โ Scribed by Rahul Mula
No coin nor oath required. For personal study only.
Preface
Table of Contents
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 8
Chapter 9
Chapter 10
Chapter 11
Chapter 12
Chapter 13
Chapter 14
Chapter 15
Chapter 16
Chapter 17
Chapter 18
Chapter 19
Chapter 20
ML Application 1
ML Application 2
ML Application 3
ML Application 4
ML Application 5
Resources
๐ SIMILAR VOLUMES
This book is written to provide a strong foundation in Machine Learning using Python libraries by providing real-life case studies and examples. It covers topics such as Foundations of Machine Learning, Introduction to Python, Descriptive Analytics and Predictive Analytics. Advanced Machine Learning
Fundamentals of Machine Learning discusses the basics of python, use of python in computing and provides a general outlook on machine learning. This book provides an insight into concepts such as linear regression with one variable, linear algebra, and linear regression with multiple inputs. The cla
Fundamentals of Machine Learning discusses the basics of python, use of python in computing and provides a general outlook on machine learning. This book provides an insight into concepts such as linear regression with one variable, linear algebra, and linear regression with multiple inputs. The cla
"The machine learning field is concerned with the question of how to create computer programs that automatically improve information. In recent years, many successful electronic learning applications have been made, from data mining systems that learn to detect fraudulent credit card transactions, f
<b>A practical guide that will help you understand the Statistical Foundations of any Machine Learning Problem.</b> <b>Key Features</b><li> Develop a Conceptual and Mathematical understanding of Statistics</li><li>Get an overview of Statistical Applications in Python</li><li>Learn how to perform