Artificial Intelligence (AI) and Machine Learning (ML) technologies have become key innovation accelerators for organizations looking for that extra edge. Machine Learning books are a great starting point for enthusiasts who want to transition to these in-demand roles. In this article we list down top machine learning books to get you started on ML journey. The increased usage of machine learning in enterprises has driven up the need for skilled professionals. Machine learning models serve up Netflix recommendations, Facebooks News Feed leverages machine learning to drum up personalized content, and Twitter utilizes machine learning to rank tweets and boost engagements.
Machine Learning is evidently a vast field and its study is one of the most enlightening tasks one could ever undertake. Today most of the business operations and innovations are done around ML and its innovative applications. A number of professionals are up-skilling themselves with advanced ML knowledge to thrive ahead in their respective fields. They are more keen on learning the offerings, advancements, experts' opinion and various nuances in context to machine learning or artificial intelligence (AI) as a whole. If you are tech-enthusiast and looking forward to learning some new ideas and innovations about machine learning, you can find plenty of comprehensive books that demonstrate and offer various skills, advice and learning opportunities.
"Machine Learning foners Second Edition has been written and designed for absolute beginners. This means plain-English explanations and no coding experience required. Where core algorithms are introduced, clear explanations and visual examples are added to make it easy and engaging to follow along at home. This major new edition features many topics not covered in the First Edition, including Cross Validation, Data Scrubbing and Ensemble Modeling."
There is much debate among scholars and practitioners about what data science is, and what it isn't. Does it deal only with big data? Is data science really that new? How is it different from statistics and analytics? One way to consider data science is as an evolutionary step in interdisciplinary fields like business analysis that incorporate computer science, modeling, statistics, analytics, and mathematics.
In this article, we will explain briefly about some of the best books that can help you understand the concepts of Machine Learning, and guide you in your journey in becoming an expert in this engaging domain. Moreover, these books are a great source of inspiration, filled with ideas and innovations, granted that you are familiar with the fundamentals of programming languages. As the title explains, if you're an absolute beginner to Machine Learning, this book should be your entry point. Requiring little to no coding or mathematical background, all the concepts in the book have been explained very clearly. Examples are followed by visuals to present the topics in a friendlier manner, for understanding the vitals of ML.