Cracking The Data Science Interview
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Author | : Maverick Lin |
Publisher | : |
Total Pages | : 120 |
Release | : 2019-12-17 |
Genre | : |
ISBN | : 9781710680133 |
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.
Author | : Kevin Huo |
Publisher | : |
Total Pages | : 290 |
Release | : 2021 |
Genre | : Big data |
ISBN | : 9780578973838 |
Author | : Nitin Suri |
Publisher | : Independently Published |
Total Pages | : 100 |
Release | : 2018-12-18 |
Genre | : |
ISBN | : 9781729223604 |
"A breakthrough in machine learning would be worth ten Microsofts." -Bill Gates Despite being one of the hottest disciplines in the Tech industry right now, Artificial Intelligence and Machine Learning remain a little elusive to most.The erratic availability of resources online makes it extremely challenging for us to delve deeper into these fields. Especially when gearing up for job interviews, most of us are at a loss due to the unavailability of a complete and uncondensed source of learning. Cracking the Machine Learning Interview Equips you with 225 of the best Machine Learning problems along with their solutions. Requires only a basic knowledge of fundamental mathematical and statistical concepts. Assists in learning the intricacies underlying Machine Learning concepts and algorithms suited to specific problems. Uniquely provides a manifold understanding of both statistical foundations and applied programming models for solving problems. Discusses key points and concrete tips for approaching real life system design problems and imparts the ability to apply them to your day to day work. This book covers all the major topics within Machine Learning which are frequently asked in the Interviews. These include: Supervised and Unsupervised Learning Classification and Regression Decision Trees Ensembles K-Nearest Neighbors Logistic Regression Support Vector Machines Neural Networks Regularization Clustering Dimensionality Reduction Feature Extraction Feature Engineering Model Evaluation Natural Language Processing Real life system design problems Mathematics and Statistics behind the Machine Learning Algorithms Various distributions and statistical tests This book can be used by students and professionals alike. It has been drafted in a way to benefit both, novices as well as individuals with substantial experience in Machine Learning. Following Cracking The Machine Learning Interview diligently would equip you to face any Machine Learning Interview.
Author | : Shrilata Murthy |
Publisher | : |
Total Pages | : 212 |
Release | : 2020-07-27 |
Genre | : |
ISBN | : 9781641379854 |
According to LinkedIn's third annual U.S. Emerging Jobs Report, the data scientist role is ranked third among the top-15 emerging jobs in the U.S. Though the field of data science has been exploding, there didn't appear to be a comprehensive resource to help data scientists navigate the interview process... until now. In Be the Outlier: How to Ace Data Science Interviews, data scientist Shrilata Murthy covers all aspects of a data science interview in today's industry. Murthy combines her own experience in the job market with expert insight from data scientists with Google, Facebook, Amazon, NASA, Aetna, MBB & Big 4 consulting firms, and many more. In this book, you'll learn... the foundational knowledge that is key to any data science interview the 100-Word Story framework for writing a stellar resume what to expect from a variety of interview styles (take-home, presentation, case study, etc.), and actionable ways to differentiate yourself from your peers. By using real-world examples, practice questions, and sample interviews, Murthy has created an easy-to-follow guide that will help you crack any data science interview. After reading Be the Outlier, get ready to land your dream job in data science.
Author | : Gayle Laakmann McDowell |
Publisher | : CreateSpace |
Total Pages | : 0 |
Release | : 2011 |
Genre | : Computer programmers |
ISBN | : 9781466208681 |
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.
Author | : Kal Mishra |
Publisher | : Createspace Independent Publishing Platform |
Total Pages | : 240 |
Release | : 2018-10-03 |
Genre | : |
ISBN | : 9781727287325 |
A collection of over 650 actual Data Scientist/Machine Learning Engineer job interview questions along with their full answers, references, and useful tips
Author | : Vamsee Puligadda |
Publisher | : Vamsee Puligadda |
Total Pages | : 151 |
Release | : |
Genre | : Computers |
ISBN | : |
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.
Author | : Shlomo Kashani |
Publisher | : |
Total Pages | : |
Release | : 2020-12-09 |
Genre | : |
ISBN | : 9781034057253 |
The book's contents is a large inventory of numerous topics relevant to DL job interviews and graduate level exams. That places this work at the forefront of the growing trend in science to teach a core set of practical mathematical and computational skills. It is widely accepted that the training of every computer scientist must include the fundamental theorems of ML, and AI appears in the curriculum of nearly every university. This volume is designed as an excellent reference for graduates of such programs.
Author | : Sergei Nakariakov |
Publisher | : CreateSpace Independent Publishing Platform |
Total Pages | : 525 |
Release | : 2014-02-07 |
Genre | : Computers |
ISBN | : 1495459802 |
Part I Algorithms and Data Structures 1 Fundamentals Approximating the square root of a number Generating Permutation Efficiently Unique 5-bit Sequences Select Kth Smallest Element The Non-Crooks Problem Is this (almost) sorted? Sorting an almost sorted list The Longest Upsequence Problem Fixed size generic array in C++ Seating Problem Segment Problems Exponentiation Searching two-dimensional sorted array Hamming Problem Constant Time Range Query Linear Time Sorting Writing a Value as the Sum of Squares The Celebrity Problem Transport Problem Find Length of the rope Switch Bulb Problem In, On or Out The problem of the balanced seg The problem of the most isolated villages 2 Arrays The Plateau Problem Searching in Two Dimensional Sequence The Welfare Crook Problem 2D Array Rotation A Queuing Problem in A Post Office Interpolation Search Robot Walk Linear Time Sorting Write as sum of consecutive positive numbers Print 2D Array in Spiral Order The Problem of the Circular Racecourse Sparse Array Trick Bulterman’s Reshuffling Problem Finding the majority Mode of a Multiset Circular Array Find Median of two sorted arrays Finding the missing integer Finding the missing number with sorted columns Re-arranging an array Switch and Bulb Problem Compute sum of sub-array Find a number not sum of subsets of array Kth Smallest Element in Two Sorted Arrays Sort a sequence of sub-sequences Find missing integer Inplace Reversing Find the number not occurring twice in an array 3 Trees Lowest Common Ancestor(LCA) Problem Spying Campaign 4 Dynamic Programming Stage Coach Problem Matrix Multiplication TSP Problem A Simple Path Problem String Edit Distance Music recognition Max Sub-Array Problem 5 Graphs Reliable distribution Independent Set Party Problem 6 Miscellaneous Compute Next Higher Number Searching in Possibly Empty Two Dimensional Sequence Matching Nuts and Bolts Optimally Random-number generation Weighted Median Compute a^n Compute a^n revisited Compute the product a × b Compute the quotient and remainder Compute GCD Computed Constrained GCD Alternative Euclid’ Algorithm Revisit Constrained GCD Compute Square using only addition and subtraction Factorization Factorization Revisited Decimal Representation Reverse Decimal Representation Solve Inequality Solve Inequality Revisited Print Decimal Representation Decimal Period Length Sequence Periodicity Problem Compute Function Emulate Division and Modulus Operations Sorting Array of Strings : Linear Time LRU data structure Exchange Prefix and Suffix 7 Parallel Algorithms Parallel Addition Find Maximum Parallel Prefix Problem Finding Ranks in Linked Lists Finding the k th Smallest Element 8 Low Level Algorithms Manipulating Rightmost Bits Counting 1-Bits Counting the 1-bits in an Array Computing Parity of a word Counting Leading/Trailing 0’s Bit Reversal Bit Shuffling Integer Square Root Newton’s Method Integer Exponentiation LRU Algorithm Shortest String of 1-Bits Fibonacci words Computation of Power of 2 Round to a known power of 2 Round to Next Power of 2 Efficient Multiplication by Constants Bit-wise Rotation Gray Code Conversion Average of Integers without Overflow Least/Most Significant 1 Bit Next bit Permutation Modulus Division Part II C++ 8 General 9 Constant Expression 10 Type Specifier 11 Namespaces 12 Misc 13 Classes 14 Templates 15 Standard Library
Author | : Jane You |
Publisher | : Createspace Independent Publishing Platform |
Total Pages | : 0 |
Release | : 2015 |
Genre | : Big data |
ISBN | : 9781511977487 |
"The era has come when data science is changing the world and everyone's life. Data Science Interviews Exposed is the first book in the industry that covers everything you need to know to prepare for a data science career: from job market overview to job roles description, from resume preparation to soft skill development, and most importantly, the real interview questions and detailed answers. We hope this book can help the candidates in the data science job market, as well as those who need guidance to begin a data science career."--Back cover.