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205 changes: 102 additions & 103 deletions SUMMARY.md
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# Summary
# Table of contents

* [Introduction to Machine Learning Interviews Book](README.md)
* [Target audience](contents/0-target-audience.md)
* [About the questions](contents/0-about-the-questions.md)
* [About the answers](contents/0-about-the-answers.md)
* [Gaming the interview process](contents/0-gaming-the-interview-process.md)
* [Acknowledgments](contents/0-acknowledgments.md)
* [About the author](contents/0-about-the-author.md)
* [Target audience](contents/0-target-audience.md)
* [About the questions](contents/0-about-the-questions.md)
* [About the answers](contents/0-about-the-answers.md)
* [Gaming the interview process](contents/0-gaming-the-interview-process.md)
* [Acknowledgments](contents/0-acknowledgments.md)
* [About the author](contents/0-about-the-author.md)
* [Part I. Overview](contents/part-i.-overview.md)
* [Chapter 1. Machine learning jobs](contents/chapter-1.-ml-jobs.md)
* [1.1 Different machine learning roles](contents/1.1-different-ml-roles.md)
* [1.1.1 Working in research vs. working in production](contents/1.1.1-working-in-research-vs.-workingin-production.md)
* [1.1.2 Research](contents/1.1.2-research.md)
* [1.1.2.1 Research vs. applied research](contents/1.1.2.1-research-vs.-applied-research.md)
* [1.1.2.2 Research scientist vs. research engineer](contents/1.1.2.2-research-scientist-vs.-research-engineer.md)
* [1.1.3 Production](contents/1.1.3-production.md)
* [1.1.3.1 Production cycle](contents/1.1.3.1-production-cycle.md)
* [1.1.3.2 Machine learning engineer vs. software engineer](contents/1.1.3.2-machine-learning-engineer-vs.-software-engineer.md)
* [1.1.3.3 Machine learning engineer vs. data scientist](contents/1.1.3.3-machine-learning-engineer-vs.-data-scientist.md)
* [1.1.3.4 Other technical roles in ML production](contents/1.1.3.4-other-technical-roles-in-ml-production.md)
* [1.1.3.5 Understanding roles and titles](contents/1.1.3.5-understanding-roles-and-titles.md)
* [1.2 Types of companies](contents/1.2-types-of-companies.md)
* [1.2.1 Applications companies vs. tooling companies](contents/1.2.1-applications-companies-vs.-tooling-companies.md)
* [1.2.2 Enterprise vs. consumer products](contents/1.2.2-enterprise-vs.-consumer-products.md)
* [1.2.3 Startups or big companies](contents/1.2.3-startups-or-big-companies.md)
* [Chapter 2. Machine learning interview process](contents/chapter-2.-machine-learning-interview-process.md)
* [2.1 Understanding the interviewers’ mindset](contents/2.1-understanding-the-interviewers’-mindset.md)
* [2.1.1 What companies want from candidates](contents/2.1.1-what-companies-want-from-candidates.md)
* [2.1.1.1 Technical skills](contents/2.1.1.1-technical-skills.md)
* [2.1.1.2 Non-technical skills](contents/2.1.1.2-non-technical-skills.md)
* [2.1.1.3 What exactly is culture fit?](contents/2.1.1.3-what-exactly-is-culture-fit.md)
* [2.1.1.4 Junior vs senior roles](contents/2.1.1.4-junior-vs-senior-roles.md)
* [2.1.1.5 Do I need a Ph.D. to work in machine learning?](contents/2.1.1.5-do-i-need-a-ph.d.-to-work-in-machine-learning.md)
* [2.1.2 How companies source candidates](contents/2.1.2-how-companies-source-candidates.md)
* [2.1.3 What signals companies look for in candidates](contents/2.1.3-what-signals-companies-look-for-in-candidates.md)
* [2.2 Interview pipeline](contents/2.2-interview-pipeline.md)
* [2.2.1 Common interview formats](contents/2.2.1-common-interview-formats.md)
* [2.2.2 Alternative interview formats](contents/2.2.2-alternative-interview-formats.md)
* [2.2.3 Interviews at big companies vs. at small companies](contents/2.2.3-interviews-at-big-companies-vs.-at-small-companies.md)
* [2.2.4 Interviews for internships vs. for full-time positions](contents/2.2.4-interviews-for-internships-vs.-for-full-time-positions.md)
* [2.3 Types of questions](contents/2.3-types-of-questions.md)
* [2.3.1 Behavioral questions](contents/2.3.1-behavioral-questions.md)
* [2.3.1.1 Background and resume](contents/2.3.1.1-background-and-resume.md)
* [2.3.1.2 Interests](contents/2.3.1.2-interests.md)
* [2.3.1.3 Communication](contents/2.3.1.3-communication.md)
* [2.3.1.4 Personality](contents/2.3.1.4-personality.md)
* [2.3.2 Questions to ask your interviewers](contents/2.3.2-questions-to-ask-your-interviewers.md)
* [2.3.3 Bad interview questions](contents/2.3.3-bad-interview-questions.md)
* [2.4 Red flags](contents/2.4-red-flags.md)
* [2.5 Timeline](contents/2.5-timeline.md)
* [2.6 Understanding your odds](contents/2.6-understanding-your-odds.md)
* [Chapter 3. After an offer](contents/chapter-3.-after-an-offer.md)
* [3.1 Compensation package](contents/3.1-compensation-package.md)
* [3.1.1 Base salary](contents/3.1.1-base-salary.md)
* [3.1.2 Equity grants](contents/3.1.2-equity-grants.md)
* [3.1.3 Bonuses](contents/3.1.3-bonuses.md)
* [3.1.4 Compensation packages at different levels](contents/3.1.4-compensation-packages-at-different-levels.md)
* [3.2 Negotiation](contents/3.2-negotiation.md)
* [3.2.1 Compensation expectations](contents/3.2.1-compensation-expectations.md)
* [3.3 Career progression](contents/3.3-career-progression.md)
* [Chapter 4. Where to start](contents/chapter-4.-where-to-start.md)
* [4.1 How long do I need for my job search?](contents/4.1-how-long-do-i-need-for-my-job-search.md)
* [4.2 How other people did it](contents/4.2-how-other-people-did-it.md)
* [4.3 Resources](contents/4.3-resources.md)
* [4.3.1 Courses](contents/4.3.1-courses.md)
* [4.3.2 Books & articles](contents/4.3.2-books-&-articles.md)
* [4.3.3 Other resources](contents/4.3.3-other-resources.md)
* [4.4 Do’s and don’ts for ML interviews](contents/4.4-do’s-and-don’ts-for-ml-interviews.md)
* [4.4.1 Do’s](contents/4.4.1-do’s.md)
* [4.4.2 Don’ts](contents/4.4.2-don’ts.md)
* [Chapter 1. Machine learning jobs](contents/chapter-1.-ml-jobs.md)
* [1.1 Different machine learning roles](contents/1.1-different-ml-roles.md)
* [1.1.1 Working in research vs. working in production](contents/1.1.1-working-in-research-vs.-workingin-production.md)
* [1.1.2 Research](contents/1.1.2-research.md)
* [1.1.2.1 Research vs. applied research](contents/1.1.2.1-research-vs.-applied-research.md)
* [1.1.2.2 Research scientist vs. research engineer](contents/1.1.2.2-research-scientist-vs.-research-engineer.md)
* [1.1.3 Production](contents/1.1.3-production.md)
* [1.1.3.1 Production cycle](contents/1.1.3.1-production-cycle.md)
* [1.1.3.2 Machine learning engineer vs. software engineer](contents/1.1.3.2-machine-learning-engineer-vs.-software-engineer.md)
* [1.1.3.3 Machine learning engineer vs. data scientist](contents/1.1.3.3-machine-learning-engineer-vs.-data-scientist.md)
* [1.1.3.4 Other technical roles in ML production](contents/1.1.3.4-other-technical-roles-in-ml-production.md)
* [1.1.3.5 Understanding roles and titles](contents/1.1.3.5-understanding-roles-and-titles.md)
* [1.2 Types of companies](contents/1.2-types-of-companies.md)
* [1.2.1 Applications companies vs. tooling companies](contents/1.2.1-applications-companies-vs.-tooling-companies.md)
* [1.2.2 Enterprise vs. consumer products](contents/1.2.2-enterprise-vs.-consumer-products.md)
* [1.2.3 Startups or big companies](contents/1.2.3-startups-or-big-companies.md)
* [Chapter 2. Machine learning interview process](contents/chapter-2.-machine-learning-interview-process.md)
* [2.1 Understanding the interviewers’ mindset](contents/2.1-understanding-the-interviewers’-mindset.md)
* [2.1.1 What companies want from candidates](contents/2.1.1-what-companies-want-from-candidates.md)
* [2.1.1.1 Technical skills](contents/2.1.1.1-technical-skills.md)
* [2.1.1.2 Non-technical skills](contents/2.1.1.2-non-technical-skills.md)
* [2.1.1.3 What exactly is culture fit?](contents/2.1.1.3-what-exactly-is-culture-fit.md)
* [2.1.1.4 Junior vs senior roles](contents/2.1.1.4-junior-vs-senior-roles.md)
* [2.1.1.5 Do I need a Ph.D. to work in machine learning?](contents/2.1.1.5-do-i-need-a-ph.d.-to-work-in-machine-learning.md)
* [2.1.2 How companies source candidates](contents/2.1.2-how-companies-source-candidates.md)
* [2.1.3 What signals companies look for in candidates](contents/2.1.3-what-signals-companies-look-for-in-candidates.md)
* [2.2 Interview pipeline](contents/2.2-interview-pipeline.md)
* [2.2.1 Common interview formats](contents/2.2.1-common-interview-formats.md)
* [2.2.2 Alternative interview formats](contents/2.2.2-alternative-interview-formats.md)
* [2.2.3 Interviews at big companies vs. at small companies](contents/2.2.3-interviews-at-big-companies-vs.-at-small-companies.md)
* [2.2.4 Interviews for internships vs. for full-time positions](contents/2.2.4-interviews-for-internships-vs.-for-full-time-positions.md)
* [2.3 Types of questions](contents/2.3-types-of-questions.md)
* [2.3.1 Behavioral questions](contents/2.3.1-behavioral-questions.md)
* [2.3.1.1 Background and resume](contents/2.3.1.1-background-and-resume.md)
* [2.3.1.2 Interests](contents/2.3.1.2-interests.md)
* [2.3.1.3 Communication](contents/2.3.1.3-communication.md)
* [2.3.1.4 Personality](contents/2.3.1.4-personality.md)
* [2.3.2 Questions to ask your interviewers](contents/2.3.2-questions-to-ask-your-interviewers.md)
* [2.3.3 Bad interview questions](contents/2.3.3-bad-interview-questions.md)
* [2.4 Red flags](contents/2.4-red-flags.md)
* [2.5 Timeline](contents/2.5-timeline.md)
* [2.6 Understanding your odds](contents/2.6-understanding-your-odds.md)
* [Chapter 3. After an offer](contents/chapter-3.-after-an-offer.md)
* [3.1 Compensation package](contents/3.1-compensation-package.md)
* [3.1.1 Base salary](contents/3.1.1-base-salary.md)
* [3.1.2 Equity grants](contents/3.1.2-equity-grants.md)
* [3.1.3 Bonuses](contents/3.1.3-bonuses.md)
* [3.1.4 Compensation packages at different levels](contents/3.1.4-compensation-packages-at-different-levels.md)
* [3.2 Negotiation](contents/3.2-negotiation.md)
* [3.2.1 Compensation expectations](contents/3.2.1-compensation-expectations.md)
* [3.3 Career progression](contents/3.3-career-progression.md)
* [Chapter 4. Where to start](contents/chapter-4.-where-to-start.md)
* [4.1 How long do I need for my job search?](contents/4.1-how-long-do-i-need-for-my-job-search.md)
* [4.2 How other people did it](contents/4.2-how-other-people-did-it.md)
* [4.3 Resources](contents/4.3-resources.md)
* [4.3.1 Courses](contents/4.3.1-courses.md)
* [4.3.2 Books & articles](contents/4.3.2-books-&-articles.md)
* [4.3.3 Other resources](contents/4.3.3-other-resources.md)
* [4.4 Do’s and don’ts for ML interviews](contents/4.4-do’s-and-don’ts-for-ml-interviews.md)
* [4.4.1 Do’s](contents/4.4.1-do’s.md)
* [4.4.2 Don’ts](contents/4.4.2-don’ts.md)
* [Part II: Questions](contents/part-ii.-questions.md)
* [Chapter 5. Math](contents/chapter-5.-math.md)
* [Notation](contents/notation.md)
* [5.1 Algebra and (little) calculus](contents/5.1-algebra-and-calculus.md)
* [5.1.1 Vectors](contents/5.1.1-vectors.md)
* [5.1.2 Matrices](contents/5.1.2-matrices.md)
* [5.1.3 Dimensionality reduction](contents/5.1.3-dimensionality-reduction.md)
* [5.1.4 Calculus and convex optimization](contents/5.1.4-calculus-and-convex-optimization.md)
* [5.2 Probability and statistics](contents/5.2-probability-and-statistics.md)
* [5.2.1 Probability](contents/5.2.1-probability.md)
* [5.2.1.1 Basic concepts to review](contents/5.2.1.1-basic-concepts-to-review.md)
* [5.2.1.2 Questions](contents/5.2.1.2-questions.md)
* [5.2.2 Stats](contents/5.2.2-stats.md)
* [Chapter 6. Computer Science](contents/chapter-6.-computer-science.md)
* [6.1 Algorithms](contents/6.1-algorithms.md)
* [6.2 Complexity and numerical analysis](contents/6.2-complexity-and-numerical-analysis.md)
* [6.3 Data](contents/6.3-data.md)
* [6.3.1 Data structures](contents/6.3.1-data-structures.md)
* [Chapter 7. Machine learning workflows](contents/chapter-7.-machine-learning-workflows.md)
* [7.1 Basics](contents/7.1-basics.md)
* [7.2 Sampling and creating training data](contents/7.2-sampling-and-creating-training-data.md)
* [7.3 Objective functions, metrics, and evaluation](contents/7.3-objective-functions,-metrics,-and-evaluation.md)
* [Chapter 8. Machine learning algorithms](contents/chapter-8.-machine-learning-algorithms.md)
* [8.1 Classical machine learning](contents/8.1-classical-machine-learning.md)
* [8.1.1 Overview: Basic algorithm](contents/8.1.1-overview:-basic-algorithm.md)
* [8.1.2 Questions](contents/8.1.2-questions.md)
* [8.2 Deep learning architectures and applications](contents/8.2-deep-learning-architectures-and-applications.md)
* [8.2.1 Natural language processing](contents/8.2.1-natural-language-processing.md)
* [8.2.2 Computer vision](contents/8.2.2-computer-vision.md)
* [8.2.3 Reinforcement learning](contents/8.2.3-reinforcement-learning.md)
* [8.2.4 Other](contents/8.2.4-other.md)
* [8.3 Training neural networks](contents/8.3-training-neural-networks.md)
* [Chapter 5. Math](contents/chapter-5.-math.md)
* [Notation](contents/notation.md)
* [5.1 Algebra and (little) calculus](contents/5.1-algebra-and-calculus.md)
* [5.1.1 Vectors](contents/5.1.1-vectors.md)
* [5.1.2 Matrices](contents/5.1.2-matrices.md)
* [5.1.3 Dimensionality reduction](contents/5.1.3-dimensionality-reduction.md)
* [5.1.4 Calculus and convex optimization](contents/5.1.4-calculus-and-convex-optimization.md)
* [5.2 Probability and statistics](contents/5.2-probability-and-statistics.md)
* [5.2.1 Probability](contents/5.2.1-probability.md)
* [5.2.1.1 Basic concepts to review](contents/5.2.1.1-basic-concepts-to-review.md)
* [5.2.1.2 Questions](contents/5.2.1.2-questions.md)
* [5.2.2 Stats](contents/5.2.2-stats.md)
* [Chapter 6. Computer Science](contents/chapter-6.-computer-science.md)
* [6.1 Algorithms](contents/6.1-algorithms.md)
* [6.2 Complexity and numerical analysis](contents/6.2-complexity-and-numerical-analysis.md)
* [6.3 Data](contents/6.3-data.md)
* [6.3.1 Data structures](contents/6.3.1-data-structures.md)
* [Chapter 7. Machine learning workflows](contents/chapter-7.-machine-learning-workflows.md)
* [7.1 Basics](contents/7.1-basics.md)
* [7.2 Sampling and creating training data](contents/7.2-sampling-and-creating-training-data.md)
* [7.3 Objective functions, metrics, and evaluation](contents/7.3-objective-functions,-metrics,-and-evaluation.md)
* [Chapter 8. Machine learning algorithms](contents/chapter-8.-machine-learning-algorithms.md)
* [8.1 Classical machine learning](contents/8.1-classical-machine-learning.md)
* [8.1.1 Overview: Basic algorithm](contents/8.1.1-overview-basic-algorithm.md)
* [8.1.2 Questions](contents/8.1.2-questions.md)
* [8.2 Deep learning architectures and applications](contents/8.2-deep-learning-architectures-and-applications.md)
* [8.2.1 Natural language processing](contents/8.2.1-natural-language-processing.md)
* [8.2.2 Computer vision](contents/8.2.2-computer-vision.md)
* [8.2.3 Reinforcement learning](contents/8.2.3-reinforcement-learning.md)
* [8.2.4 Other](contents/8.2.4-other.md)
* [8.3 Training neural networks](contents/8.3-training-neural-networks.md)
* [Appendix](contents/appendix.md)
* [A. For interviewers](contents/a.-for-interviewers.md)
* [The zen of interviews](contents/the-zen-of-interviews.md)
* [B. Building your network](contents/b.-building-your-network.md)

* [A. For interviewers](contents/a.-for-interviewers.md)
* [The zen of interviews](contents/the-zen-of-interviews.md)
* [B. Building your network](contents/b.-building-your-network.md)
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The geometric interpretation of the dot product of two vectors provides a measure of simmilarity in direction of the two vectors
or in other words quantifies how much one vector is going in the direction of the other
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