Machine Learning: Fundamentals and Applications

Machine learning (ML) is a subfield of computer science that focuses on the study and development of methods that enable computers to "learn." These are methods that make use of data in order to enhance a computer's performance on a certain set of tasks.

How You Will Benefit

(I) Insights, and validations about the following topics:

Chapter 1: Machine learning

Chapter 2: Big data

Chapter 3: Self-driving car

Chapter 4: Unsupervised learning

Chapter 5: Supervised learning

Chapter 6: Statistical learning theory

Chapter 7: Computational learning theory

Chapter 8: Automated machine learning

Chapter 9: Differentiable programming

Chapter 10: Reinforcement learning

(II) Answering the public top questions about machine learning.

(III) Real world examples for the usage of machine learning in many fields.

(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of machine learning' technologies.

Who This Book Is For

Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of machine learning.