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Machine Learning Interview Questions and Answers

De (autor): Geoffrey Ziskovin

Coperta cărții 'Machine Learning Interview Questions and Answers - Geoffrey Ziskovin'
Machine Learning Interview Questions and Answers

De (autor): Geoffrey Ziskovin

This book "Machine Learning Interview Questions & Answers" is a must practice book to test your knowledge in the field of Machine Learning.

The field is vast and Industry takes a different approach. The questions are tailored specific to the Industry Interviews which tests your theoretical knowledge of the field relevant for practical work.

This book has over 120 MCQs (Multiple Choice Questions). Each one is provided with the correct answer along with in-depth explanation. So, your revision will be complete as you attempt the problems. This includes core questions from Deep Learning important for ML Interviews as well.

This book covers all core topics through the carefully selected set of Interview Questions:

  • Core ML techniques like Classification, Regression, Clustering
  • Core ML concepts like Supervised, Unsupervised and Semi-Supervised Learning, Naïve Bayes, Central Limit Theorem, Standardization and much more.
  • Deep Learning (DL) concepts relevant for ML Interviews like CNN, RNN, fundamental operations like Fully Connected Layer and much more.

One must go through this book at regular intervals to test their knowledge and identify loopholes in their understanding so that it can be corrected in time.

Book: Machine Learning Interview Questions & Answers
Authors (2): Aditya Chatterjee, Geoffrey Ziskovin
About the authors:

  • Aditya Chatterjee is an Independent Researcher, Technical Author and the Founding Member of OPENGENUS, a scientific community focused on Computing Technology.
  • Geoffrey Ziskovin is an American Software Engineer with an experience of over 30 years. He has interviewed over 700 candidates worldwide for various Fortune 500 companies.
Contributors (2): Benjamin QoChuk: Computer Science Researcher, Inventor and Software Developer; Leandro Baruch: IT Project Services Specialist at UNHCR (UN Refugee Agency)

Published: May 2022 (Edition 1)
Publisher: (c) OpenGenus

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This book "Machine Learning Interview Questions & Answers" is a must practice book to test your knowledge in the field of Machine Learning.

The field is vast and Industry takes a different approach. The questions are tailored specific to the Industry Interviews which tests your theoretical knowledge of the field relevant for practical work.

This book has over 120 MCQs (Multiple Choice Questions). Each one is provided with the correct answer along with in-depth explanation. So, your revision will be complete as you attempt the problems. This includes core questions from Deep Learning important for ML Interviews as well.

This book covers all core topics through the carefully selected set of Interview Questions:

  • Core ML techniques like Classification, Regression, Clustering
  • Core ML concepts like Supervised, Unsupervised and Semi-Supervised Learning, Naïve Bayes, Central Limit Theorem, Standardization and much more.
  • Deep Learning (DL) concepts relevant for ML Interviews like CNN, RNN, fundamental operations like Fully Connected Layer and much more.

One must go through this book at regular intervals to test their knowledge and identify loopholes in their understanding so that it can be corrected in time.

Book: Machine Learning Interview Questions & Answers
Authors (2): Aditya Chatterjee, Geoffrey Ziskovin
About the authors:

  • Aditya Chatterjee is an Independent Researcher, Technical Author and the Founding Member of OPENGENUS, a scientific community focused on Computing Technology.
  • Geoffrey Ziskovin is an American Software Engineer with an experience of over 30 years. He has interviewed over 700 candidates worldwide for various Fortune 500 companies.
Contributors (2): Benjamin QoChuk: Computer Science Researcher, Inventor and Software Developer; Leandro Baruch: IT Project Services Specialist at UNHCR (UN Refugee Agency)

Published: May 2022 (Edition 1)
Publisher: (c) OpenGenus

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