Machine Learning with New AI: Algorithms and Artificial Intelligence

How to Use This Book
This book is for Students, data scientists, Machine Learning experts and professionals, and researchers in academia who want to understand the understanding of machine learning approaches/algorithms and AI in practice using Python.

Machine learning is an old science, but it is gaining fresh momentum due to the generation of huge amounts of data from heterogeneous sources at a rapid pace. The variety of forms is something which is the headlines in the industry. While many machine learning algorithms have been around for a long time and carry its legacy from statistics, the ability to automatically apply complex mathematical calculations and logic to Big Data with the help of sophisticated analytics over and over, faster and faster, is a recent development.

This book presents some common machine learning and associated technologies and their relationship. It will help the reader grab some important concepts.
Table of Contents
1.The Evolution of Data Science and the Information Age
2.General Introduction to Machine Learning
3.The Practical Concepts of Machine Learning
4.Artificial Intelligence: The New AI Rising
5.I Am the Future: Machine Learning in Action
6.Why We Are Interested In Machine Learning
7.Overview of Machine Learning in Healthcare
8.Innovation, KPIs, Best Practices, and More for Machine Learning
9.Learning Clusters and Recommendations
10.Best Practices for Machine Learning
11.Convolutional Neural Networks
12.Recurrent Neural Networks
13.Natural Language Processing and ChatBots
14.Why Data Scientists use Machine Learning
15.Machine Learning Summary: You and Your Data

The Evolution of Data Science and the Information Age
Data science is a broad umbrella term that encompasses a number of disciplines and concepts including big data, artificial intelligence (AI), data mining and machine learning.

The discipline of studying large volumes of data, known as ‘data science’, is relatively new and has grown hand-in-hand with the development and wide adoption of computers. Prior to computers, data was calculated and processed by hand under the umbrella of ‘statistics’ or what we might now refer to as ‘classical statistics’.

Machine Learning Business Opportunities
Technologies, like machine learning, Big Data analytics, and cloud and cognitive computing, are transforming the business models of almost all the industries across the globe. The old ways of doing business are changing rapidly. Enterprises across all the vertical and horizontal markets are finding novel ways to operate and innovate their businesses. This creates new business opportunities and avenues for digital and physical enterprises. Entrepreneurship is on the rise; innovative minds are creating new business models around the new generation of technologies. The result of this traction is showcased in the form of optimized operations, reduced costs, improved services, and/or launching new products. Lots of companies are using ML for their financial benefits and achieving business completeness:

About the Author
Narendra Mohan Mittal is the Founder and Chairman of Thesis Scientist and he is working in the field of Data Science/big data/machine learning/deep learning space. He has more than 10 years in Research and Teaching and he is very active in the Big Data, Data Science and Machine learning.