Machine Learning Interviews: Kickstart Your Machine Learning and Data Career

Cover....1 Copyright....3 Table of Contents....4 Preface....12 Why Machine Learning Jobs?....15 Who This Book Is For....17 What This Book Is Not....17 Conventions Used in This Book....18 O’Reilly Online Learning....19 How to Contact Us....19 Acknowledgments....20 Chapter 1. Machine Learning Roles and the Interview Process....22 Overview of This Book....23 A Brief History of Machine Learning and Data Science Job Titles....24 Job Titles Requiring ML Experience....27 Machine Learning Lifecycle....29 Startups....30 Larger ML Teams....31 The Three Pillars of Machine Learning Roles....33 Machine Learning Algorithms and Data Intuition: Ability to Adapt....33 Programming and Software Engineering: Ability to Build....34 Execution and Communication: Ability to Get Things Done in a Team....34 Clearing Minimum Requirements in the Three ML Pillars....35 Machine Learning Skills Matrix....36 Introduction to ML Job Interviews....38 Machine Learning Job-Interview Process....39 Applying for Jobs Through Websites or Job Boards....40 Resume Screening of Website or Job-Board Applications....41 Applying via a Referral....43 Preinterview Checklist....44 Recruiter Screening....46 Overview of Main Interview Loop....47 Summary....49 Chapter 2. Machine Learning Job Application and Resume....50 Where Are the Jobs?....50 ML Job Application Guide....51 Your Effectiveness per Application....51 Job Referrals....52 Networking....56 Machine Learning Resume Guide....58 Take Inventory of Your Past Experience....58 Overview of Resume Sections....60 Tailoring Your Resume to Your Desired Role(s)....65 Final Resume Touch-ups....69 Applying to Jobs....70 Vetting Job Postings....70 Mapping Your Skills and Experience to the ML Skills Matrix....70 Tracking Applications....72 Additional Job Application Materials, Credentials, and FAQ....73 Do You Need a Project Portfolio?....73 Do Online Certifications Help?....74 FAQ: How Many Pages Should My Resume Be?....77 FAQ: Should I Format My Resume for ATS (Applicant Tracking Systems)?....78 Next Steps....79 Browsing Job Postings....79 Identifying the Gaps Between Your Current Skills and Target Roles....79 Summary....82 Chapter 3. Technical Interview: Machine Learning Algorithms....84 Overview of the Machine Learning Algorithms Technical Interview....84 Statistical and Foundational Techniques....86 Summarizing Independent and Dependent Variables....87 Defining Models....88 Summarizing Linear Regression....89 Defining Training and Test Set Splits....92 Defining Model Underfitting and Overfitting....93 Summarizing Regularization....94 Sample Interview Questions on Foundational Techniques....95 Supervised, Unsupervised, and Reinforcement Learning....97 Defining Labeled Data....98 Summarizing Supervised Learning....99 Defining Unsupervised Learning....99 Summarizing Semisupervised and Self-Supervised Learning....100 Summarizing Reinforcement Learning....102 Sample Interview Questions on Supervised and Unsupervised Learning....102 Natural Language Processing Algorithms....107 Summarizing NLP Underlying Concepts....108 Summarizing Long Short-Term Memory Networks....109 Summarizing Transformer Models....110 Summarizing BERT Models....110 Summarizing GPT Models....112 Going Further....112 Sample Interview Questions on NLP....113 Recommender System Algorithms....116 Summarizing Collaborative Filtering....116 Summarizing Explicit and Implicit Ratings....117 Summarizing Content-Based Recommender Systems....117 User-Based/Item-Based Versus Content-Based Recommender Systems....118 Summarizing Matrix Factorization....118 Sample Interview Questions on Recommender Systems....119 Reinforcement Learning Algorithms....122 Summarizing Reinforcement Learning Agents....123 Summarizing Q-Learning....125 Summarizing Model-Based Versus Model-Free Reinforcement Learning....127 Summarizing Value-Based Versus Policy-Based Reinforcement Learning....128 Summarizing On-Policy Versus Off-Policy Reinforcement Learning....129 Sample Interview Questions on Reinforcement Learning....129 Computer Vision Algorithms....132 Summarizing Common Image Datasets....133 Summarizing Convolutional Neural Networks (CNNs)....134 Summarizing Transfer Learning....135 Summarizing Generative Adversarial Networks....135 Summarizing Additional Computer Vision Use Cases....137 Sample Interview Questions on Image Recognition....139 Summary....140 Chapter 4. Technical Interview: Model Training and Evaluation....142 Defining a Machine Learning Problem....143 Data Preprocessing and Feature Engineering....145 Introduction to Data Acquisition....145 Introduction to Exploratory Data Analysis....146 Introduction to Feature Engineering....147 Sample Interview Questions on Data Preprocessing and Feature Engineering....153 The Model Training Process....154 The Iteration Process in Model Training....154 Defining the ML Task....156 Overview of Model Selection....157 Overview of Model Training....159 Sample Interview Questions on Model Selection and Training....161 Model Evaluation....162 Summary of Common ML Evaluation Metrics....163 Trade-offs in Evaluation Metrics....166 Additional Methods for Offline Evaluation....167 Model Versioning....168 Sample Interview Questions on Model Evaluation....169 Summary....170 Chapter 5. Technical Interview: Coding....172 Starting from Scratch: Learning Roadmap If You Don’t Know Python....173 Pick Up a Book or Course That’s Easy to Understand....174 Start with Easy Questions on LeetCode, HackerRank, or Your Platform of Choice....174 Set a Measurable Target and Practice, Practice, Practice....175 Try Out ML-Related Python Packages....175 Coding Interview Success Tips....175 Think Out Loud....175 Control the Flow....176 Your Interviewer Can Help You Out....177 Optimize Your Environment....178 Interviews Require Energy!....178 Python Coding Interview: Data- and ML-Related Questions....179 Sample Data- and ML-Related Interview and Questions....179 FAQs for Data- and ML-Focused Interviews....187 Resources for Data and ML Interview Questions....188 Python Coding Interview: Brainteaser Questions....189 Patterns for Brainteaser Programming Questions....190 Resources for Brainteaser Programming Questions....198 SQL Coding Interview: Data-Related Questions....199 Resources for SQL Coding Interview Questions....201 Roadmaps for Preparing for Coding Interviews....201 Coding Interview Roadmap Example: Four Weeks, University Student....202 Coding Interview Roadmap Example: Six Months, Career Transition....204 Coding Interview Roadmap: Create Your Own!....205 Summary....205 Chapter 6. Technical Interview: Model Deployment and End-to-End ML....206 Model Deployment....207 The Main Experience Gap for New Entrants into the ML Industry....207 Should Data Scientists and MLEs Know This?....209 End-to-End Machine Learning....210 Cloud Environments and Local Environments....212 Overview of Model Deployment....215 Additional Tooling to Know....218 On-Device Machine Learning....219 Interviews for Roles Focused on Model Training....219 Model Monitoring....221 Monitoring Setups....221 ML-Related Monitoring Metrics....224 Overview of Cloud Providers....224 GCP....225 AWS....226 Microsoft Azure....227 Developer Best Practices for Interviews....227 Version Control....228 Dependency Management....229 Code Review....229 Tests....230 Additional Technical Interview Components....230 Machine Learning Systems Design Interview....231 Technical Deep-Dive Interview....234 Take-Home Exercise Tips....235 Product Sense....235 Sample Interview Questions on MLOps....236 Summary....238 Chapter 7. Behavioral Interviews....240 Behavioral Interview Questions and Responses....241 Use the STAR Method to Answer Behavioral Questions....242 Enhance Your Answers with the Hero’s Journey Method....243 Best Practices and Feedback from an Interviewer’s Perspective....246 Common Behavioral Questions and Recommendations....248 Questions About Communication Skills....248 Questions About Collaboration and Teamwork....249 Questions on How You Respond to Feedback....250 Questions on Dealing with Challenges and Learning New Skills....250 Questions About the Company....251 Questions About Work Projects....251 Free-Form Questions....252 Behavioral Interview Best Practices....252 How to Answer Behavioral Questions If You Don’t Have Relevant Work Experience....253 Senior+ Behavioral Interview Tips....254 Specific Preparation Examples for Big Tech....256 Amazon....256 Meta/Facebook....257 Alphabet/Google....258 Netflix....259 Summary....260 Chapter 8. Tying It All Together: Your Interview Roadmap....262 Interview Preparation Checklist....262 Interview Roadmap Template....263 Efficient Interview Preparation....265 Become a Better Learner....265 Time Management and Accountability....267 Avoid Burnout: It Is Costly....269 Impostor Syndrome....270 Summary....271 Chapter 9. Post-Interview and Follow-up....272 Post-Interview Steps....272 Take Notes of What You Remember from the Interview....273 Make Sure You’re Not Missing Important Information....273 Should You Send a Thank-You Email to the Interviewer?....273 Thank-You Note Template....273 How Long Should You Wait After the Interview for a Response Before Following Up?....275 What to Do Between Interviews....275 How to Respond to Rejections....275 Template for Rejection Responses....275 Job Applications Are a Funnel....276 Update and Customize Your Resume and Test Variations....277 Steps of the Offer Stage....278 Let Other Interviews-in-Progress Know You’ve Gotten an Offer....278 What to Do If the Offer Response Timeline Is Very Short....278 Understand Your Offer....279 First 30/60/90 Days of Your New ML Job....282 Gain Domain Knowledge....283 Gain Code Knowledge....283 Meet Relevant People....284 Help Improve the Onboarding Documentation....284 Keep Track of Your Achievements....284 Summary....285 Epilogue....286 Index....288 About the Author....308 Colophon....308