When you want to find data science interview, you may need to consider between many choices. Finding the best data science interview is not an easy task. In this post, we create a very short list about top 8 the best data science interview for you. You can check detail product features, product specifications and also our voting for each product. Let’s start with following top 8 data science interview:
Reviews
1. Elements of Programming Interviews in Python: The Insiders' Guide
Description
This is the Python version of our book. See the website for links to the C++and Javaversion.Take great care to buy the latest version: bit.ly/buyingEPI
Since different candidates have different time constraints, EPI includes astudy guidewith severalscenarios,ranging from weekendHackathontosemester long preparationwith a recommended a subset of problems for each scenario.
All problems are classified in terms of theirdifficulty leveland include manyvariantsto help you apply what you have learned more widely.
2. A collection of Advanced Data Science and Machine Learning Interview Questions Solved in Python and Spark (II): Hands-on Big Data and Machine ... Programming Interview Questions) (Volume 7)
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A Collection of Advanced Data Science and Machine Learning Interview Questions Solved in Python and Spark II Hands On Big Data and Machine LearningDescription
A collection of Machine Learning interview questions in Python and Spark3. Cracking the Coding Interview: 189 Programming Questions and Solutions
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Cracking the Coding Interview 189 Programming Questions and SolutionsDescription
I am not a recruiter. I am a software engineer. And as such, I know what it's like to be asked to whip up brilliant algorithms on the spot and then write flawless code on a whiteboard. I've been through this as a candidate and as an interviewer.Cracking the Coding Interview, 6th Edition is here to help you through this process, teaching you what you need to know and enabling you to perform at your very best. I've coached and interviewed hundreds of software engineers. The result is this book.
Learn how to uncover the hints and hidden details in a question, discover how to break down a problem into manageable chunks, develop techniques to unstick yourself when stuck, learn (or re-learn) core computer science concepts, and practice on 189 interview questions and solutions.
These interview questions are real; they are not pulled out of computer science textbooks. They reflect what's truly being asked at the top companies, so that you can be as prepared as possible. WHAT'S INSIDE?
- 189 programming interview questions, ranging from the basics to the trickiest algorithm problems.
- A walk-through of how to derive each solution, so that you can learn how to get there yourself.
- Hints on how to solve each of the 189 questions, just like what you would get in a real interview.
- Five proven strategies to tackle algorithm questions, so that you can solve questions you haven't seen.
- Extensive coverage of essential topics, such as big O time, data structures, and core algorithms.
- A behind the scenes look at how top companies like Google and Facebook hire developers.
- Techniques to prepare for and ace the soft side of the interview: behavioral questions.
- For interviewers and companies: details on what makes a good interview question and hiring process.
4. Grokking Algorithms: An illustrated guide for programmers and other curious people
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Grokking Algorithms An Illustrated Guide for Programmers and Other Curious PeopleDescription
Summary
Grokking Algorithms is a fully illustrated, friendly guide that teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python.
Learning about algorithms doesn't have to be boring! Get a sneak peek at the fun, illustrated, and friendly examples you'll find in Grokking Algorithms on Manning Publications' YouTube channel.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the Technology
An algorithm is nothing more than a step-by-step procedure for solving a problem. The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to understand them but refuse to slog through dense multipage proofs, this is the book for you. This fully illustrated and engaging guide makes it easy to learn how to use the most important algorithms effectively in your own programs.
About the Book
Grokking Algorithms is a friendly take on this core computer science topic. In it, you'll learn how to apply common algorithms to the practical programming problems you face every day. You'll start with tasks like sorting and searching. As you build up your skills, you'll tackle more complex problems like data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python. By the end of this book, you will have mastered widely applicable algorithms as well as how and when to use them.
What's Inside
- Covers search, sort, and graph algorithms
- Over 400 pictures with detailed walkthroughs
- Performance trade-offs between algorithms
- Python-based code samples
About the Reader
This easy-to-read, picture-heavy introduction is suitable for self-taught programmers, engineers, or anyone who wants to brush up on algorithms.
About the Author
Aditya Bhargava is a Software Engineer with a dual background in Computer Science and Fine Arts. He blogs on programming at adit.io.
Table of Contents
- Introduction to algorithms
- Selection sort
- Recursion
- Quicksort
- Hash tables
- Breadth-first search
- Dijkstra's algorithm
- Greedy algorithms
- Dynamic programming
- K-nearest neighbors
5. Journey to Data Scientist: Interviews with More Than Twenty Amazing Data Scientists
Description
When author Kate Strachnyi wanted to learn more about data science, she went straight to the source.
In a series of more than twenty interviews, she asks leading data scientists questions about starting in the field and the future of the industry.
With their stories, learn about
- the many different positions available for data scientists,
- the criteria recruiters look for when hiring,
- the best options for building your portfolio,
- the recruitment and interviewing process,
- the typical workday for a data scientist,
- the changing industry and its impact on other industries,
- the wide variety of projects that use data science, and
- the skills that can complement and improve your work.
Strachnyis interview subjects include team members from some of the worlds largest organizations, including LinkedIn, Pinterest, Bloomberg, and IBM. These men and women graciously explain how they fell in love with data science and list the must-have skills that would make you an invaluable member of a team. Their advice gives you invaluable insight into the world of data science and the best ways you yourself can contribute to amazing research projects and the development of new technology.
6. Data Science from Scratch: First Principles with Python
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Data Science from Scratch First Principles with PythonDescription
Data science libraries, frameworks, modules, and toolkits are great for doing data science, but theyre also a good way to dive into the discipline without actually understanding data science. In this book, youll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch.
If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Todays messy glut of data holds answers to questions no ones even thought to ask. This book provides you with the know-how to dig those answers out.
- Get a crash course in Python
- Learn the basics of linear algebra, statistics, and probabilityand understand how and when they're used in data science
- Collect, explore, clean, munge, and manipulate data
- Dive into the fundamentals of machine learning
- Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering
- Explore recommender systems, natural language processing, network analysis, MapReduce, and databases
7. The Data Science Handbook: Advice and Insights from 25 Amazing Data Scientists
Description
The Data Science Handbook contains interviews with 25 of the world s best data scientists. We sat down with them, had in-depth conversations about their careers, personal stories, perspectives on data science and life advice. In The Data Science Handbook, you will find war stories from DJ Patil, US Chief Data Officer and one of the founders of the field. You ll learn industry veterans such as Kevin Novak and Riley Newman, who head the data science teams at Uber and Airbnb respectively. You ll also read about rising data scientists such as Clare Corthell, who crafted her own open source data science masters program. This book is perfect for aspiring or current data scientists to learn from the best. It s a reference book packed full of strategies, suggestions and recipes to launch and grow your own data science career.8. Data Science Interviews Exposed
Description
Data Science Interviews Exposed offers data science career advice and REAL interview questions to help you get the six-figures salary jobs! A data science job is extremely rewarding. It empowers to you make real impact in the world! And besides, it offers competitive salaries, and it develops your creative as well as quantitative skills. No wonder the data science job is rated as one of the sexist jobs in 21st century. So what you are waiting for ?- Are you still wondering how to join data science work force ?
- Are you lost in the tremendous amount of online data science courses and resources ?
- Are you endlessly searching online to find data science interview questions and answers?
- This book is written by data science professionals from Facebook, LinkedIn, Amazon, Google and Microsoft, with years of first hand working and interviewing experience.
- This is the first book in the industry that systematically covers everything for preparing for a data science career and interviews, and with real interview questions and detailed answers.
- This book provides both career guidance for entry level candidates as well as interview questions practice for intermediate candidates.
- Probability Theory
- Statistical Inference
- Dataset Manipulation
- Product, Metrics and Analytics
- Experiment Design
- Coding
- Machine Learning
- Brain Teasers
Here is a full list of topics:
Introduction
This chapter presents an overview to the data science job market and the book organization.
Find the Right Job Roles
Get confused about the various data science job titles? This chapter provides a detailed description for each of them, the differences among them, as well as the guidance for choosing the one that suits you the most.
Find the Right Experience
Don't know how to prepare yourself with the right experience to meet the job requirements and your career goals? This chapter helps you to identify the experience you need to land your dream position. It also provides suggestions for new graduates as well as candidates from a different industry who want to transfer to data science field.
Get Ready for the Interviews
Think you have a clear goal and have possessed all the required skill sets, but just don't know how to get job interviews? This chapter walks you through how to build good resumes and professional profiles that would bring you the right exposure to the right person -- recruiters and hiring managers.
Polish Your Soft Skills
Heard of your competent peers failing job interviews and want to know why? This chapter reveals the secrets that most companies don t talk about publicly -- the soft skills. What are behavior questions, why are they important, how do you prepare for them? You will find the answer here.
Technical Interview Questions
An interview is not a pop quiz. You should take the time to practice on real interview problems and learn their patterns. This chapter lists eight major topics that are frequently covered by data science job interviews, associated with example interview questions for each of them. All of them are either real interview questions or adapted from real interview questions:
This chapter attaches the solutions and thought process for each question in the previous chapter. We hope the readers can grasp the key points behind each of them, hence be able to apply the approaches to other similar questions in the real interviews.