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Python Machine Learning: A Hands-On Beginner's Guide to Effectively Understand Artificial Neural Networks and Machine Learning Using Python (With Tips and Tricks)
Authors: James Deep
ISBN-10 书号: 1705586686
ISBN-13 书号: 9781705586686
Publisher Finelybook 出版日期: 2019-11-08
pages 页数: 116 pages
Book Description
If you are ready to know the link between Python Programming and Machine Learning,then keep reading.
The concept of Artificial Intelligence is regarded by many as the way of the future. It covers vast areas of study and complements almost every aspect of human life. The evolution of intelligent machines has been on the rise as experts try to outsmart each other in innovation. Many business models,health organizations,government units,and many more,have adopted one or two practices that incorporate automation into their daily activities.
As part of Artificial Intelligence,Machine Learning has seen significant applications across significant sectors of the economies of the world. To date,almost every aspect of our life has elements of Machine Learning. From the phones we use to the retail stores we do our shopping at,the areas covered by Machine Learning applications are drastically increasing by the day.
This technique has helped the developers of software to create high-tech apps that predict changes in the market,sort large amounts of data,and offer solutions to major real-world problems. As much the trends are evident on the ground,the theoretical perspective remains an isolated area to many. Scaling through Machine Learning requires some knowledge of programming. In general terms,you need a platform to gain an understanding of the topic and hone your skills in the same.
Python Machine Learning covers the concept of Machine Learning,in a detailed but well elaborate language of presentation. The topic may not be simple but is very worthwhile as long as you understand the fundamental concepts that underlie Machine Learning.
Inside this book you will find:
Types of ML
Essential Libraries for ML
Regression Analysis
The Perceptron trick
…and many more amazing and interesting topics!
This book takes readers on a knowledge trip through solved examples,tips,tricks,and visualized content. It will not only create an appetite for more but also give readers what they need to know about Machine Learning!
Introduction
Chapter 1: Introduction: A Historical Overview of Machine Learning
Chapter 2: Types Of Machine Learning
Chapter 3: Use of Python in Machine Learning
Chapter 4: Essential Libraries For ML In Python
Chapter 5: Regression Analysis (Linear Regression and Logistic Regression)
Chapter 6. The Perceptron
Chapter 7: Useful Platforms For Python Programming
Chapter 8: Decision Trees
Chapter 9: K-Nearest Neighbors(KNN)
Chapter 10: Random Forest Algorithms with Python
Chapter 11: Perceptron Algorithm
Conclusion
