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| atlassian data scientist interview: Cracking the Coding Interview Gayle Laakmann McDowell, 2011 Now in the 5th edition, Cracking the Coding Interview gives you the interview preparation you need to get the top software developer jobs. This book provides: 150 Programming Interview Questions and Solutions: From binary trees to binary search, this list of 150 questions includes the most common and most useful questions in data structures, algorithms, and knowledge based questions. 5 Algorithm Approaches: Stop being blind-sided by tough algorithm questions, and learn these five approaches to tackle the trickiest problems. Behind the Scenes of the interview processes at Google, Amazon, Microsoft, Facebook, Yahoo, and Apple: Learn what really goes on during your interview day and how decisions get made. Ten Mistakes Candidates Make -- And How to Avoid Them: Don't lose your dream job by making these common mistakes. Learn what many candidates do wrong, and how to avoid these issues. Steps to Prepare for Behavioral and Technical Questions: Stop meandering through an endless set of questions, while missing some of the most important preparation techniques. Follow these steps to more thoroughly prepare in less time. |
| atlassian data scientist interview: 500 Data Science Interview Questions and Answers Vamsee Puligadda, Get that job, you aspire for! Want to switch to that high paying job? Or are you already been preparing hard to give interview the next weekend? Do you know how many people get rejected in interviews by preparing only concepts but not focusing on actually which questions will be asked in the interview? Don't be that person this time. This is the most comprehensive Data Science interview questions book that you can ever find out. It contains: 500 most frequently asked and important Data Science interview questions and answers Wide range of questions which cover not only basics in Data Science but also most advanced and complex questions which will help freshers, experienced professionals, senior developers, testers to crack their interviews. |
| atlassian data scientist interview: Jira 8 Essentials Patrick Li, 2019-02-28 Publisher's note: A new sixth edition, updated with enhanced Jira 8.21 and Data Center features has now been published. Key Features Work on agile projects in Jira from both the administrator and end user's perspective Explore the improved Scrum and Kanban board and backlog Work through exercises at the end of each chapter to reinforce your skills Book Description Atlassian Jira enables effective bug tracking for your software and mobile applications and provides tools to track and manage tasks for your projects. Jira Essentials is a comprehensive guide, now updated to Jira 8 to include enhanced features such as updates to Scrum and Kanban UI, additional search capabilities, and changes to Jira Service Desk. The book starts by explaining how to plan and set up a new Jira 8 instance from scratch before getting you acquainted with key features such as emails, workflows, business processes, and much more. You'll then understand Jira's data hierarchy and how to design and work with projects. Since Jira is used for issue management, this book delves into the different issues that can arise in your projects. You'll explore fields, including custom fields, and learn to use them for more effective data collection. You'll create new screens from scratch and customize them to suit your requirements. The book also covers workflows and business processes, and guides you in setting up incoming and outgoing mail servers. Toward the end, you'll study Jira's security model and Jira Service Desk, which allows you to run Jira as a support portal. By the end of this Jira book, you will be able to implement Jira 8 in your projects with ease. What you will learn Understand Jira's data hierarchy and how to design and work with projects in Jira Use Jira for agile software projects, business process management, customer service support, and more Understand issues and work with them Design both system and custom fields to behave differently under different contexts Create and design your own screens and apply them to different project and issue types Gain an understanding of the workflow and its various components Set up both incoming and outgoing mail servers to work with e-mails Who this book is for This book will be especially useful for project managers but it's also intended for other Jira users, including developers, and any other industry besides software development, who would like to leverage Jira's powerful task management and workflow features to better manage their business processes. |
| atlassian data scientist interview: Jira Software Essentials Patrick Li, 2018-01-30 Explore Jira Software to manage your projects proficiently Key Features Plan and manage projects effortlessly with Jira Software by integrating it with other applications Improve your team's performance with Scrum and Kanban, together with agile methodology Easy-to-follow learning guide to install Jira Software and understand how it fits in with Atlassian Jira Book Description Jira Software is an agile project management tool that supports any agile methodology, be it scrum, Kanban, or your own unique flavour. From agile boards to reports, you can plan, track, and manage all your agile software development projects from a single tool. Jira Software brings the power of agile methodology to Atlassian Jira. This second edition of JIRA Agile Essentials, will help you dive straight into the action, exploring critical agile terminologies and concepts in the context of Jira Software. You will learn how to plan, track, and release great software. This book will teach you how to install and run Jira Software and set it up to run with Scrum and Kanban. It will also teach you to use Jira Software your way and run projects beyond the out-of-box Scrum and Kanban way, including a hybrid approach of both the methodologies and other options that come with Jira Software. Later, you will learn how to integrate it with the tools you are already using and enhance Jira with add-ons such as Confluence. You will learn to stay connected with your team from anywhere to ensure great development. Jira Software has numerous deployment options in the cloud, on your own infrastructure, or at a massive scale. You will be introduced to Bitbucket, Atlassian’s distributed version control system, which integrates seamlessly with Jira, allowing your team to work within the two applications as one harmonious environment. With this practical guide, you will develop a great working knowledge of Jira Software and your project management will become much more efficient. What you will learn Understand the basics and agile methodologies of Jira software Use Jira Software in a Scrum environment Manage and run Jira Software projects beyond the out of box Scrum and Kanban way Combine Scrum and Kanban and use other project management options beyond just agile Customize Jira Software’s various features and options as per your requirements Work with Jira Agile offline, and plan and forecast projects with agile portfolio Integrate Jira Agile with Confluence and Bitbucket Who this book is for If you want to get started with Jira Software and learn how to run your Jira projects the agile way, then this is the perfect book for you. You will need to be familiar with the basics of Jira, both from an end user's and an administrator's perspective. Experience with workflows, custom fields, and other administrative functions of Jira will be useful. |
| atlassian data scientist interview: Automate Everyday Tasks in Jira Gareth Cantrell, 2021-01-22 Learn how to automate tasks and create rules in Jira with the help of different use cases Key FeaturesAutomate daily repetitive and tedious tasks without coding experienceDiscover how to automate processes in the Jira family including Jira software, Jira Service Desk, and Jira CoreExplore different use cases to understand automation features in JiraBook Description Atlassian Jira makes it easier to track the progress of your projects, but it can lead to repetitive and time-consuming tasks for teams. No-code automation will enable you to increase productivity by automating these tasks. Automate Everyday Tasks in Jira provides a hands-on approach to implementation and associated methodologies that will have you up and running and productive in no time. You will start by learning how automation in Jira works, along with discovering best practices for writing automation rules. Then you'll be introduced to the building blocks of automation, including triggers, conditions, and actions, before moving on to advanced rule-related techniques. After you've become familiar with the techniques, you'll find out how to integrate with external tools, such as GitHub, Slack, and Microsoft Teams, all without writing a single line of code. Toward the end, you'll also be able to employ advanced rules to create custom notifications and integrate with external systems. By the end of this Jira book, you'll have gained a thorough understanding of automation rules and learned how to use them to automate everyday tasks in Jira without using any code. What you will learnUnderstand the basic concepts of automation such as triggers, conditions, and actionsFind out how to use if–then scenarios and conditions to automate your processes with practical examplesUse smart values to achieve complex and more powerful automationImplement use cases in a practical way, including automation with Slack, Microsoft Teams, GitHub, and BitbucketDiscover best practices for writing and maintaining automation rulesExplore techniques for debugging rules and solving common issuesWho this book is for This book is for Jira administrators and project managers who want to learn about automation capabilities provided in Jira. Familiarity with Jira and working knowledge of workflows and project configurations is required. |
| atlassian data scientist interview: Programming Collective Intelligence Toby Segaran, 2007-08-16 Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it. Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains: Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details. -- Dan Russell, Google Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths. -- Tim Wolters, CTO, Collective Intellect |
| atlassian data scientist interview: Software Engineering at Google Titus Winters, Tom Manshreck, Hyrum Wright, 2020-02-28 Today, software engineers need to know not only how to program effectively but also how to develop proper engineering practices to make their codebase sustainable and healthy. This book emphasizes this difference between programming and software engineering. How can software engineers manage a living codebase that evolves and responds to changing requirements and demands over the length of its life? Based on their experience at Google, software engineers Titus Winters and Hyrum Wright, along with technical writer Tom Manshreck, present a candid and insightful look at how some of the worldâ??s leading practitioners construct and maintain software. This book covers Googleâ??s unique engineering culture, processes, and tools and how these aspects contribute to the effectiveness of an engineering organization. Youâ??ll explore three fundamental principles that software organizations should keep in mind when designing, architecting, writing, and maintaining code: How time affects the sustainability of software and how to make your code resilient over time How scale affects the viability of software practices within an engineering organization What trade-offs a typical engineer needs to make when evaluating design and development decisions |
| atlassian data scientist interview: Machine Learning for Hackers Drew Conway, John Myles White, 2012-02-13 If you’re an experienced programmer interested in crunching data, this book will get you started with machine learning—a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation. Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you’ll learn how to analyze sample datasets and write simple machine learning algorithms. Machine Learning for Hackers is ideal for programmers from any background, including business, government, and academic research. Develop a naïve Bayesian classifier to determine if an email is spam, based only on its text Use linear regression to predict the number of page views for the top 1,000 websites Learn optimization techniques by attempting to break a simple letter cipher Compare and contrast U.S. Senators statistically, based on their voting records Build a “whom to follow” recommendation system from Twitter data |
| atlassian data scientist interview: The Robotic Process Automation Handbook Tom Taulli, 2020-02-28 While Robotic Process Automation (RPA) has been around for about 20 years, it has hit an inflection point because of the convergence of cloud computing, big data and AI. This book shows you how to leverage RPA effectively in your company to automate repetitive and rules-based processes, such as scheduling, inputting/transferring data, cut and paste, filling out forms, and search. Using practical aspects of implementing the technology (based on case studies and industry best practices), you’ll see how companies have been able to realize substantial ROI (Return On Investment) with their implementations, such as by lessening the need for hiring or outsourcing. By understanding the core concepts of RPA, you’ll also see that the technology significantly increases compliance – leading to fewer issues with regulations – and minimizes costly errors. RPA software revenues have recently soared by over 60 percent, which is the fastest ramp in the tech industry, and they are expected to exceed $1 billion by the end of 2019. It is generally seamless with legacy IT environments, making it easier for companies to pursue a strategy of digital transformation and can even be a gateway to AI. The Robotic Process Automation Handbook puts everything you need to know into one place to be a part of this wave. What You'll Learn Develop the right strategy and planDeal with resistance and fears from employeesTake an in-depth look at the leading RPA systems, including where they are most effective, the risks and the costsEvaluate an RPA system Who This Book Is For IT specialists and managers at mid-to-large companies |
| atlassian data scientist interview: Database Management Systems P.S. Gill, 2010-09-30 The book is intended to provide an insight into the DBMS concepts. An effort has been made to familiarize the readers with the concepts of database normalization, concurrency control, deadlock handling and recovery etc., which are extremely vital for a clear understanding of DBMS. To familiarize the readers with the equivalence amongst Relational Algebra, Tuple Relational Calculus, and SQL, a large number of equivalent queries have been provided. The concepts of normalization have been elaborated very systematically by fully covering the underlying concepts of functional dependencies, multi-valued dependencies, join dependencies, loss-less-join decomposition, dependency-preserving decomposition etc. It is hoped that with the help of the information provided in the text, a reader will be able to design a flawless database. Also, the concepts of serializabilty, concurrency control, deadlock handling and log-based recovery have been covered in full detail. An overview has also been provided of the issues related to distributed-databases. |
| atlassian data scientist interview: The Improv Handbook Tom Salinsky, Deborah Frances-White, 2017-10-19 The Improv Handbook is the most comprehensive, smart, helpful and inspiring guide to improv available today. Applicable to comedians, actors, public speakers and anyone who needs to think on their toes, it features a range of games, interviews, descriptions and exercises that illuminate and illustrate the exciting world of improvised performance. First published in 2008, this second edition features a new foreword by comedian Mike McShane, as well as new exercises on endings, managing blind offers and master-servant games, plus new and expanded interviews with Keith Johnstone, Neil Mullarkey, Jeffrey Sweet and Paul Rogan. The Improv Handbook is a one-stop guide to the exciting world of improvisation. Whether you're a beginner, an expert, or would just love to try it if you weren't too scared, The Improv Handbook will guide you every step of the way. |
| atlassian data scientist interview: Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World Bruce Schneier, 2015-03-02 “Bruce Schneier’s amazing book is the best overview of privacy and security ever written.”—Clay Shirky Your cell phone provider tracks your location and knows who’s with you. Your online and in-store purchasing patterns are recorded, and reveal if you're unemployed, sick, or pregnant. Your e-mails and texts expose your intimate and casual friends. Google knows what you’re thinking because it saves your private searches. Facebook can determine your sexual orientation without you ever mentioning it. The powers that surveil us do more than simply store this information. Corporations use surveillance to manipulate not only the news articles and advertisements we each see, but also the prices we’re offered. Governments use surveillance to discriminate, censor, chill free speech, and put people in danger worldwide. And both sides share this information with each other or, even worse, lose it to cybercriminals in huge data breaches. Much of this is voluntary: we cooperate with corporate surveillance because it promises us convenience, and we submit to government surveillance because it promises us protection. The result is a mass surveillance society of our own making. But have we given up more than we’ve gained? In Data and Goliath, security expert Bruce Schneier offers another path, one that values both security and privacy. He brings his bestseller up-to-date with a new preface covering the latest developments, and then shows us exactly what we can do to reform government surveillance programs, shake up surveillance-based business models, and protect our individual privacy. You'll never look at your phone, your computer, your credit cards, or even your car in the same way again. |
| atlassian data scientist interview: Dream Teams Shane Snow, 2018-06-05 Award-winning entrepreneur and journalist Shane Snow reveals the counterintuitive reasons why so many partnerships and groups break down--and why some break through. The best teams are more than the sum of their parts, but why does collaboration so often fail to fulfill this promise? In Dream Teams, Snow takes us on an adventure through history, neuroscience, psychology, and business, exploring what separates groups that simply get by together from those that get better together. You'll learn: * How ragtag teams--from soccer clubs to startups to gangs of pirates--beat the odds throughout history. * Why DaimlerChrysler flopped while the Wu-Tang Clan succeeded, and the surprising factor behind most failed mergers, marriages, and partnerships. * What the Wright Brothers' daily arguments can teach us about group problem solving. * Pioneering women in law enforcement, unlikely civil rights collaborators, and underdog armies that did the incredible together. * The team players behind great social movements in history, and the science of becoming open-minded. Provocative and entertaining, Dream Teams is a landmark work that will change the way we think about people, progress, and collaboration. |
| atlassian data scientist interview: Brief Joseph McCormack, 2024-11-20 Get heard by being clear and concise The only way to survive in business today is to be a lean communicator. Busy executives expect you to respect and manage their time more effectively than ever. You need to do the groundwork to make your message tight and to the point. The average professional receives 304 emails per week and checks their smartphones 36 times an hour and 38 hours a week. This inattention has spread to every part of life. The average attention span has shrunk from 12 seconds in 2000 to eight in 2012. So, throw them a lifeline and be brief. Author Joe McCormack tackles the challenges of inattention, interruptions, and impatience that every professional faces. His proven B.R.I.E.F. approach, which stands for Background, Relevance, Information, Ending, and Follow up, helps simplify and clarify complex communication. BRIEF will help you summarize lengthy information, tell a short story, harness the power of infographics and videos, and turn monologue presentations into controlled conversations. Details the B.R.I.E.F. approach to distilling your message into a brief presentation Written by the founder and CEO of Sheffield Marketing Partners, which specializes in message and narrative development, who is also a recognized expert in Narrative Mapping, a technique that helps clients achieve a clearer and more concise message Long story short: BRIEF will help you gain the muscle you need to eliminate wasteful words and stand out from the rest. Be better. Be brief. |
| atlassian data scientist interview: The Data Warehouse Toolkit Ralph Kimball, Margy Ross, 2011-08-08 This old edition was published in 2002. The current and final edition of this book is The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition which was published in 2013 under ISBN: 9781118530801. The authors begin with fundamental design recommendations and gradually progress step-by-step through increasingly complex scenarios. Clear-cut guidelines for designing dimensional models are illustrated using real-world data warehouse case studies drawn from a variety of business application areas and industries, including: Retail sales and e-commerce Inventory management Procurement Order management Customer relationship management (CRM) Human resources management Accounting Financial services Telecommunications and utilities Education Transportation Health care and insurance By the end of the book, you will have mastered the full range of powerful techniques for designing dimensional databases that are easy to understand and provide fast query response. You will also learn how to create an architected framework that integrates the distributed data warehouse using standardized dimensions and facts. |
| atlassian data scientist interview: You Don't Know JS: Scope & Closures Kyle Simpson, 2014-03-10 No matter how much experience you have with JavaScript, odds are you don’t fully understand the language. This concise yet in-depth guide takes you inside scope and closures, two core concepts you need to know to become a more efficient and effective JavaScript programmer. You’ll learn how and why they work, and how an understanding of closures can be a powerful part of your development skillset. Like other books in the You Don’t Know JS series, Scope and Closures dives into trickier parts of the language that many JavaScript programmers simply avoid. Armed with this knowledge, you can achieve true JavaScript mastery. Learn about scope, a set of rules to help JavaScript engines locate variables in your code Go deeper into nested scope, a series of containers for variables and functions Explore function- and block-based scope, “hoisting”, and the patterns and benefits of scope-based hiding Discover how to use closures for synchronous and asynchronous tasks, including the creation of JavaScript libraries |
| atlassian data scientist interview: Practical Internet of Things Security Brian Russell, Drew Van Duren, 2016-06-29 A practical, indispensable security guide that will navigate you through the complex realm of securely building and deploying systems in our IoT-connected world About This Book Learn to design and implement cyber security strategies for your organization Learn to protect cyber-physical systems and utilize forensic data analysis to beat vulnerabilities in your IoT ecosystem Learn best practices to secure your data from device to the cloud Gain insight into privacy-enhancing techniques and technologies Who This Book Is For This book targets IT Security Professionals and Security Engineers (including pentesters, security architects and ethical hackers) who would like to ensure security of their organization's data when connected through the IoT. Business analysts and managers will also find it useful. What You Will Learn Learn how to break down cross-industry barriers by adopting the best practices for IoT deployments Build a rock-solid security program for IoT that is cost-effective and easy to maintain Demystify complex topics such as cryptography, privacy, and penetration testing to improve your security posture See how the selection of individual components can affect the security posture of the entire system Use Systems Security Engineering and Privacy-by-design principles to design a secure IoT ecosystem Get to know how to leverage the burdgening cloud-based systems that will support the IoT into the future. In Detail With the advent of Intenret of Things (IoT), businesses will be faced with defending against new types of threats. The business ecosystem now includes cloud computing infrastructure, mobile and fixed endpoints that open up new attack surfaces, a desire to share information with many stakeholders and a need to take action quickly based on large quantities of collected data. . It therefore becomes critical to ensure that cyber security threats are contained to a minimum when implementing new IoT services and solutions. . The interconnectivity of people, devices, and companies raises stakes to a new level as computing and action become even more mobile, everything becomes connected to the cloud, and infrastructure is strained to securely manage the billions of devices that will connect us all to the IoT. This book shows you how to implement cyber-security solutions, IoT design best practices and risk mitigation methodologies to address device and infrastructure threats to IoT solutions. This book will take readers on a journey that begins with understanding the IoT and how it can be applied in various industries, goes on to describe the security challenges associated with the IoT, and then provides a set of guidelines to architect and deploy a secure IoT in your Enterprise. The book will showcase how the IoT is implemented in early-adopting industries and describe how lessons can be learned and shared across diverse industries to support a secure IoT. Style and approach This book aims to educate readers on key areas in IoT security. It walks readers through engaging with security challenges and then provides answers on how to successfully manage IoT security and build a safe infrastructure for smart devices. After reading this book, you will understand the true potential of tools and solutions in order to build real-time security intelligence on IoT networks. |
| atlassian data scientist interview: Effective DevOps Jennifer Davis, Ryn Daniels, 2016-05-30 Some companies think that adopting devops means bringing in specialists or a host of new tools. With this practical guide, you’ll learn why devops is a professional and cultural movement that calls for change from inside your organization. Authors Ryn Daniels and Jennifer Davis provide several approaches for improving collaboration within teams, creating affinity among teams, promoting efficient tool usage in your company, and scaling up what works throughout your organization’s inflection points. Devops stresses iterative efforts to break down information silos, monitor relationships, and repair misunderstandings that arise between and within teams in your organization. By applying the actionable strategies in this book, you can make sustainable changes in your environment regardless of your level within your organization. Explore the foundations of devops and learn the four pillars of effective devops Encourage collaboration to help individuals work together and build durable and long-lasting relationships Create affinity among teams while balancing differing goals or metrics Accelerate cultural direction by selecting tools and workflows that complement your organization Troubleshoot common problems and misunderstandings that can arise throughout the organizational lifecycle Learn from case studies from organizations and individuals to help inform your own devops journey |
| atlassian data scientist interview: Artificial Intelligence for HR Ben Eubanks, 2018-12-03 HR professionals need to get to grips with artificial intelligence and the way it's changing the world of work. From using natural language processing to ensure job adverts are free from bias and gendered language to implementing chatbots to enhance the employee experience, AI has created a variety of opportunities for the HR function. Artificial Intelligence for HR empowers HR professionals to leverage this potential and use AI to improve efficiency and develop a talented and productive workforce. Outlining the current technology landscape as well as the latest AI developments, this book ensures that HR professionals fully understand what AI is and what it means for HR in practice. Covering everything from recruitment and retention to employee engagement and learning and development, Artificial Intelligence for HR outlines the value AI can add to HR. It also features discussions on the challenges that can arise from AI and how to deal with them, including data privacy, algorithmic bias and how to develop the skills of a workforce with the rise of automation, robotics and machine learning in order to make it more human, not less. Packed with practical advice, research and case studies from global organizations including Uber, IBM and Unilever, this book will equip HR professionals with the knowledge they need to leverage AI to recruit and develop a successful workforce and help their businesses thrive in the future. |
| atlassian data scientist interview: Coding Interview Questions Narasimha Karumanchi, 2012-05 Coding Interview Questions is a book that presents interview questions in simple and straightforward manner with a clear-cut explanation. This book will provide an introduction to the basics. It comes handy as an interview and exam guide for computer scientists. Programming puzzles for interviews Campus Preparation Degree/Masters Course Preparation Big job hunters: Apple, Microsoft, Google, Amazon, Yahoo, Flip Kart, Adobe, IBM Labs, Citrix, Mentor Graphics, NetApp, Oracle, Webaroo, De-Shaw, Success Factors, Face book, McAfee and many more Reference Manual for working people Topics Covered: Programming BasicsIntroductionRecursion and BacktrackingLinked Lists Stacks Queues Trees Priority Queue and HeapsGraph AlgorithmsSortingSearching Selection Algorithms [Medians] Symbol TablesHashing String Algorithms Algorithms Design Techniques Greedy Algorithms Divide and Conquer Algorithms Dynamic Programming Complexity Classes Design Interview Questions Operating System Concepts Computer Networking Basics Database Concepts Brain Teasers NonTechnical Help Miscellaneous Concepts Note: If you already have Data Structures and Algorithms Made Easy no need to buy this. |
| atlassian data scientist interview: Advanced Analytics with Spark Sandy Ryza, Uri Laserson, Sean Owen, Josh Wills, 2015-04-02 In this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example. You’ll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply common techniques—classification, collaborative filtering, and anomaly detection among others—to fields such as genomics, security, and finance. If you have an entry-level understanding of machine learning and statistics, and you program in Java, Python, or Scala, you’ll find these patterns useful for working on your own data applications. Patterns include: Recommending music and the Audioscrobbler data set Predicting forest cover with decision trees Anomaly detection in network traffic with K-means clustering Understanding Wikipedia with Latent Semantic Analysis Analyzing co-occurrence networks with GraphX Geospatial and temporal data analysis on the New York City Taxi Trips data Estimating financial risk through Monte Carlo simulation Analyzing genomics data and the BDG project Analyzing neuroimaging data with PySpark and Thunder |
| atlassian data scientist interview: Version Control with Git Jon Loeliger, Matthew McCullough, 2012-08-14 Get up to speed on Git for tracking, branching, merging, and managing code revisions. Through a series of step-by-step tutorials, this practical guide takes you quickly from Git fundamentals to advanced techniques, and provides friendly yet rigorous advice for navigating the many functions of this open source version control system. This thoroughly revised edition also includes tips for manipulating trees, extended coverage of the reflog and stash, and a complete introduction to the GitHub repository. Git lets you manage code development in a virtually endless variety of ways, once you understand how to harness the system’s flexibility. This book shows you how. Learn how to use Git for several real-world development scenarios Gain insight into Git’s common-use cases, initial tasks, and basic functions Use the system for both centralized and distributed version control Learn how to manage merges, conflicts, patches, and diffs Apply advanced techniques such as rebasing, hooks, and ways to handle submodules Interact with Subversion (SVN) repositories—including SVN to Git conversions Navigate, use, and contribute to open source projects though GitHub |
| atlassian data scientist interview: Data Analytics Basics Simplilearn, 2020-12-14 Data analytics is increasingly becoming a key element in shaping a company’s business strategy. Today, data influences every decision made by an organization, and this is driving the wide-scale adoption of data analytics, including machine learning technologies and artificial intelligence solutions. The heightened focus is propelling a surge in data analytics spending, reflected in various studies conducted by leading market research firms. The field of data analytics offers some amazing salaries and is not only the hottest IT job, but it is also one of the best-paying jobs in the world. This guide aims at providing the readers with everything they need to know about the data analytics field, basic terminologies, key concepts, real-life use cases, skills you must master in order to scale up your career, and training and certifications you might need to reach your dream job. |
| atlassian data scientist interview: Top 100 Tricky Java Interview Questions Knowledge Powerhouse, 2016-07-21 This book contains tricky and nasty Java interview questions that an interviewer asks in Java technology interview. It is a compilation of questions after attending dozens of Java interviews in top-notch companies like- Google, Facebook, Ebay, Amazon etc. You can save time by reading questions as well as answers from the book. Sample questions are: How can you determine if JVM is 32-bit or 64-bit from Java Program? What is the right data type to represent Money (like Dollar/Pound) in Java? Is ++ operation thread-safe in Java? |
| atlassian data scientist interview: Statistics in a Nutshell Sarah Boslaugh, 2012-11-15 A clear and concise introduction and reference for anyone new to the subject of statistics. |
| atlassian data scientist interview: Business Analysis for Beginners Mohamed Elgendy, 2014-12-09 Business Analysis for Beginners is a comprehensive hands-on guide to jump-starting your BA career in four weeks. The book empowers you to gain a complete understanding of business analysis fundamental concepts and unlock the value of a business analyst to an organization in identifying problems and opportunities and finding solutions. Learn how to define the business needs and apply the most effective tools and techniques to elicit, analyze and communicate requirements with business stakeholders. Business analysis in a nutshell - gain a comprehensive understanding of business analysis fundamental concepts and understand the value of a business analyst to an organization in identifying problems and opportunities and finding solutions.Scope definition & requirements management techniques - learn how to define the business needs and the most effective tools and techniques to elicit, analyze and communicate requirements with business stakeholders. Your BA toolkit - in addition to our step-by-step guide to all business analysis tasks, this book provides a thorough explanation of the different models & methodologies of Software Development Life Cycle (SDLC) and business process modeling. Our guide to kick-starting your BA career - we have included virtually every type of interview question you might face. After each chapter, you will find an interview cheat sheet to help you ace interview rounds and land your BA role. |
| atlassian data scientist interview: Pandas Cookbook Theodore Petrou, 2017-10-23 Over 95 hands-on recipes to leverage the power of pandas for efficient scientific computation and data analysis About This Book Use the power of pandas to solve most complex scientific computing problems with ease Leverage fast, robust data structures in pandas to gain useful insights from your data Practical, easy to implement recipes for quick solutions to common problems in data using pandas Who This Book Is For This book is for data scientists, analysts and Python developers who wish to explore data analysis and scientific computing in a practical, hands-on manner. The recipes included in this book are suitable for both novice and advanced users, and contain helpful tips, tricks and caveats wherever necessary. Some understanding of pandas will be helpful, but not mandatory. What You Will Learn Master the fundamentals of pandas to quickly begin exploring any dataset Isolate any subset of data by properly selecting and querying the data Split data into independent groups before applying aggregations and transformations to each group Restructure data into tidy form to make data analysis and visualization easier Prepare real-world messy datasets for machine learning Combine and merge data from different sources through pandas SQL-like operations Utilize pandas unparalleled time series functionality Create beautiful and insightful visualizations through pandas direct hooks to Matplotlib and Seaborn In Detail This book will provide you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way. The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands like one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through practical situations that you are highly likely to encounter. Many advanced recipes combine several different features across the pandas library to generate results. Style and approach The author relies on his vast experience teaching pandas in a professional setting to deliver very detailed explanations for each line of code in all of the recipes. All code and dataset explanations exist in Jupyter Notebooks, an excellent interface for exploring data. |
| atlassian data scientist interview: The Future of Work Darrell M. West, 2018-05-15 Looking for ways to handle the transition to a digital economy Robots, artificial intelligence, and driverless cars are no longer things of the distant future. They are with us today and will become increasingly common in coming years, along with virtual reality and digital personal assistants. As these tools advance deeper into everyday use, they raise the question—how will they transform society, the economy, and politics? If companies need fewer workers due to automation and robotics, what happens to those who once held those jobs and don't have the skills for new jobs? And since many social benefits are delivered through jobs, how are people outside the workforce for a lengthy period of time going to earn a living and get health care and social benefits? Looking past today's headlines, political scientist and cultural observer Darrell M. West argues that society needs to rethink the concept of jobs, reconfigure the social contract, move toward a system of lifetime learning, and develop a new kind of politics that can deal with economic dislocations. With the U.S. governance system in shambles because of political polarization and hyper-partisanship, dealing creatively with the transition to a fully digital economy will vex political leaders and complicate the adoption of remedies that could ease the transition pain. It is imperative that we make major adjustments in how we think about work and the social contract in order to prevent society from spiraling out of control. This book presents a number of proposals to help people deal with the transition from an industrial to a digital economy. We must broaden the concept of employment to include volunteering and parenting and pay greater attention to the opportunities for leisure time. New forms of identity will be possible when the job no longer defines people's sense of personal meaning, and they engage in a broader range of activities. Workers will need help throughout their lifetimes to acquire new skills and develop new job capabilities. Political reforms will be necessary to reduce polarization and restore civility so there can be open and healthy debate about where responsibility lies for economic well-being. This book is an important contribution to a discussion about tomorrow—one that needs to take place today. |
| atlassian data scientist interview: What Color is Your Parachute? Richard Nelson Bolles, 1972 |
| atlassian data scientist interview: Doing Data Science Cathy O'Neil, Rachel Schutt, 2013-10-09 Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science. Topics include: Statistical inference, exploratory data analysis, and the data science process Algorithms Spam filters, Naive Bayes, and data wrangling Logistic regression Financial modeling Recommendation engines and causality Data visualization Social networks and data journalism Data engineering, MapReduce, Pregel, and Hadoop Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course. |
| atlassian data scientist interview: Git for Teams Emma Jane Hogbin Westby, 2015-08-24 Annotation A guide to the popular version control system, this book walks Git users through the source control implications of how a team is structured, and how the software is delivered to clients. The book then covers not just how to use popular work flow strategies, such as GitFlow, but why, and under what circumstances, these strategies should be applied. |
| atlassian data scientist interview: Cracking the Data Science Interview Maverick Lin, 2019-12-17 Cracking the Data Science Interview is the first book that attempts to capture the essence of data science in a concise, compact, and clean manner. In a Cracking the Coding Interview style, Cracking the Data Science Interview first introduces the relevant concepts, then presents a series of interview questions to help you solidify your understanding and prepare you for your next interview. Topics include: - Necessary Prerequisites (statistics, probability, linear algebra, and computer science) - 18 Big Ideas in Data Science (such as Occam's Razor, Overfitting, Bias/Variance Tradeoff, Cloud Computing, and Curse of Dimensionality) - Data Wrangling (exploratory data analysis, feature engineering, data cleaning and visualization) - Machine Learning Models (such as k-NN, random forests, boosting, neural networks, k-means clustering, PCA, and more) - Reinforcement Learning (Q-Learning and Deep Q-Learning) - Non-Machine Learning Tools (graph theory, ARIMA, linear programming) - Case Studies (a look at what data science means at companies like Amazon and Uber) Maverick holds a bachelor's degree from the College of Engineering at Cornell University in operations research and information engineering (ORIE) and a minor in computer science. He is the author of the popular Data Science Cheatsheet and Data Engineering Cheatsheet on GCP and has previous experience in data science consulting for a Fortune 500 company focusing on fraud analytics. |
| atlassian data scientist interview: Deep Learning with TensorFlow 2 and Keras Antonio Gulli, Amita Kapoor, Sujit Pal, 2019-12-27 Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devices Key FeaturesIntroduces and then uses TensorFlow 2 and Keras right from the startTeaches key machine and deep learning techniquesUnderstand the fundamentals of deep learning and machine learning through clear explanations and extensive code samplesBook Description Deep Learning with TensorFlow 2 and Keras, Second Edition teaches neural networks and deep learning techniques alongside TensorFlow (TF) and Keras. You’ll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow is the machine learning library of choice for professional applications, while Keras offers a simple and powerful Python API for accessing TensorFlow. TensorFlow 2 provides full Keras integration, making advanced machine learning easier and more convenient than ever before. This book also introduces neural networks with TensorFlow, runs through the main applications (regression, ConvNets (CNNs), GANs, RNNs, NLP), covers two working example apps, and then dives into TF in production, TF mobile, and using TensorFlow with AutoML. What you will learnBuild machine learning and deep learning systems with TensorFlow 2 and the Keras APIUse Regression analysis, the most popular approach to machine learningUnderstand ConvNets (convolutional neural networks) and how they are essential for deep learning systems such as image classifiersUse GANs (generative adversarial networks) to create new data that fits with existing patternsDiscover RNNs (recurrent neural networks) that can process sequences of input intelligently, using one part of a sequence to correctly interpret anotherApply deep learning to natural human language and interpret natural language texts to produce an appropriate responseTrain your models on the cloud and put TF to work in real environmentsExplore how Google tools can automate simple ML workflows without the need for complex modelingWho this book is for This book is for Python developers and data scientists who want to build machine learning and deep learning systems with TensorFlow. This book gives you the theory and practice required to use Keras, TensorFlow 2, and AutoML to build machine learning systems. Some knowledge of machine learning is expected. |
| atlassian data scientist interview: Business Intelligence Demystified Anoop Kumar V K, 2021-09-25 Clear your doubts about Business Intelligence and start your new journey KEY FEATURES ● Includes successful methods and innovative ideas to achieve success with BI. ● Vendor-neutral, unbiased, and based on experience. ● Highlights practical challenges in BI journeys. ● Covers financial aspects along with technical aspects. ● Showcases multiple BI organization models and the structure of BI teams. DESCRIPTION The book demystifies misconceptions and misinformation about BI. It provides clarity to almost everything related to BI in a simplified and unbiased way. It covers topics right from the definition of BI, terms used in the BI definition, coinage of BI, details of the different main uses of BI, processes that support the main uses, side benefits, and the level of importance of BI, various types of BI based on various parameters, main phases in the BI journey and the challenges faced in each of the phases in the BI journey. It clarifies myths about self-service BI and real-time BI. The book covers the structure of a typical internal BI team, BI organizational models, and the main roles in BI. It also clarifies the doubts around roles in BI. It explores the different components that add to the cost of BI and explains how to calculate the total cost of the ownership of BI and ROI for BI. It covers several ideas, including unconventional ideas to achieve BI success and also learn about IBI. It explains the different types of BI architectures, commonly used technologies, tools, and concepts in BI and provides clarity about the boundary of BI w.r.t technologies, tools, and concepts. The book helps you lay a very strong foundation and provides the right perspective about BI. It enables you to start or restart your journey with BI. WHAT YOU WILL LEARN ● Builds a strong conceptual foundation in BI. ● Gives the right perspective and clarity on BI uses, challenges, and architectures. ● Enables you to make the right decisions on the BI structure, organization model, and budget. ● Explains which type of BI solution is required for your business. ● Applies successful BI ideas. WHO THIS BOOK IS FOR This book is a must-read for business managers, BI aspirants, CxOs, and all those who want to drive the business value with data-driven insights. TABLE OF CONTENTS 1. What is Business Intelligence? 2. Why do Businesses need BI? 3. Types of Business Intelligence 4. Challenges in Business Intelligence 5. Roles in Business Intelligence 6. Financials of Business Intelligence 7. Ideas for Success with BI 8. Introduction to IBI 9. BI Architectures 10. Demystify Tech, Tools, and Concepts in BI |
| atlassian data scientist interview: Introduction to Reliable Distributed Programming Rachid Guerraoui, Luís Rodrigues, 2006-05-01 In modern computing a program is usually distributed among several processes. The fundamental challenge when developing reliable distributed programs is to support the cooperation of processes required to execute a common task, even when some of these processes fail. Guerraoui and Rodrigues present an introductory description of fundamental reliable distributed programming abstractions as well as algorithms to implement these abstractions. The authors follow an incremental approach by first introducing basic abstractions in simple distributed environments, before moving to more sophisticated abstractions and more challenging environments. Each core chapter is devoted to one specific class of abstractions, covering reliable delivery, shared memory, consensus and various forms of agreement. This textbook comes with a companion set of running examples implemented in Java. These can be used by students to get a better understanding of how reliable distributed programming abstractions can be implemented and used in practice. Combined, the chapters deliver a full course on reliable distributed programming. The book can also be used as a complete reference on the basic elements required to build reliable distributed applications. |
| atlassian data scientist interview: Agile Game Development with Scrum Clinton Keith, 2010-05-23 Deliver Better Games Faster, On Budget—And Make Game Development Fun Again! Game development is in crisis—facing bloated budgets, impossible schedules, unmanageable complexity, and death march overtime. It’s no wonder so many development studios are struggling to survive. Fortunately, there is a solution. Scrum and Agile methods are already revolutionizing development outside the game industry. Now, long-time game developer Clinton Keith shows exactly how to successfully apply these methods to the unique challenges of game development. Keith has spent more than fifteen years developing games, seven of them with Scrum and agile methods. Drawing on this unparalleled expertise, he shows how teams can use Scrum to deliver games more efficiently, rapidly, and cost-effectively; craft games that offer more entertainment value; and make life more fulfilling for development teams at the same time. You’ll learn to form successful agile teams that incorporate programmers, producers, artists, testers, and designers—and promote effective collaboration within and beyond those teams, throughout the entire process. From long-range planning to progress tracking and continuous integration, Keith offers dozens of tips, tricks, and solutions—all based firmly in reality and hard-won experience. Coverage includes Understanding Scrum’s goals, roles, and practices in the context of game development Communicating and planning your game’s vision, features, and progress Using iterative techniques to put your game into a playable state every two to four weeks— even daily Helping all team participants succeed in their roles Restoring stability and predictability to the development process Managing ambiguous requirements in a fluid marketplace Scaling Scrum to large, geographically distributed development teams Getting started: overcoming inertia and integrating Scrum into your studio’s current processes Increasingly, game developers and managers are recognizing that things can’t go on the way they have in the past. Game development organizations need a far better way to work. Agile Game Development with Scrum gives them that—and brings the profitability, creativity, and fun back to game development. |
| atlassian data scientist interview: Machine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021) Rajiv Misra, Rudrapatna K. Shyamasundar, Amrita Chaturvedi, Rana Omer, 2021-09-29 This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2021) is intended to be used as a reference book for researchers and practitioners in the disciplines of computer science, electronics and telecommunication, information science, and electrical engineering. Machine learning and Big data analytics represent a key ingredients in the industrial applications for new products and services. Big data analytics applies machine learning for predictions by examining large and varied data sets—i.e., big data—to uncover hidden patterns, unknown correlations, market trends, customer preferences, and other useful information that can help organizations make more informed business decisions. |
| atlassian data scientist interview: Sociology Michael D. Hughes, Carolyn J. Kroehler, 2005 |
| atlassian data scientist interview: The Data Science Handbook Carl Shan, Henry Wang, William Chen, Max Song, 2015-05-03 The Data Science Handbook is a curated collection of 25 candid, honest and insightful interviews conducted with some of the world's top data scientists.In this book, you'll hear how the co-creator of the term 'data scientist' thinks about career and personal success. You'll hear from a young woman who created her own data scientist curriculum, subsequently landing her a role in the field. Readers of this book will be left with war stories, wisdom and |
| atlassian data scientist interview: Curating Research Data Lisa R. Johnston, 2016-11-01 Data are becoming the proverbial coin of the digital realm: a research commodity that might purchase reputation credit in a disciplinary culture of data sharing, or buy transparency when faced with funding agency mandates or publisher scrutiny. Unlike most monetary systems, however, digital data can flow in all too great an abundance. Not only does this currency actually grow on trees, but it comes from animals, books, thoughts, and each of us! And that is what makes data curation so essential. The abundance of digital research data challenges library and information science professionals to harness this flow of information streaming from research discovery and scholarly pursuit and preserve the unique evidence for future use. Volume One of Curating Research Data explores the variety of reasons, motivations, and drivers for why data curation services are needed in the context of academic and disciplinary data repository efforts. Twelve chapters, divided into three parts, take an in-depth look at the complex practice of data curation as it emerges around us. Part I sets the stage for data curation by describing current policies, data sharing cultures, and collaborative efforts currently underway that impact potential services. Part II brings several key issues, such as cost recovery and marketing strategy, into focus for practitioners when considering how to put data curation services in action. Finally, Part III describes the full lifecycle of data by examining the ethical and practical reuse issues that data curation practitioners must consider as we strive to prepare data for the future. Digital data is ubiquitous and rapidly reshaping how scholarship progresses now and into the future. The information expertise of librarians can help ensure the resiliency of digital data, and the information it represents, by addressing how the meaning, integrity, and provenance of digital data generated by researchers today will be captured and conveyed to future researchers. |
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