Machine Learning for Beginners: A Complete and Phased Beginner's Guide to Learning and Understanding Machine Learning and Artificial Intelligence

Are you fascinated about machine learning and AI and you don't know where to start? Have you ever heard people talking about Machine Learning but you only have a vague idea of the actual meaning? Do you want to understand how machine learning could simplify your daily life? Imagine a world where computing systems understand people and the world around us them to a point where they can notice patterns, collect data, interpret it and give recommendations to solve real world problems with high level of precision. It sounds like science fiction but it is happening in healthcare, agriculture, cyber security, facial recognition, targeting and retargeting customers in online advertising, recommending specific products, stories, videos, text etc., self-driving cars, real time pricing, predicting human behavior and much more. Now imagine you being one of the people behind the code; the people who get these advanced systems to work the way they do. Would it be a dream come true for you? By virtue that you are reading this, it is clear that you have some special liking for this advanced tech and would want to learn how you can be one of the people behind the code. Even if not, you probably want to be able to understand the inner workings of these systems. The concept may sound extremely out there and advanced but it won't be if you follow this guide, which takes an easy to follow, beginner friendly language to help you to understand the ins and outs of machine learning! Here is a summary of what this book will teach you: The basics of machine learning, including what it is, how machine learning has evolved over the years, the application of machine learning in today's world and the future of machine learningHow machine learning is beneficial in today's worldThe different approaches to machine learning, including unsupervised, supervised, reinforcement learning method, semi-supervised machine learning and many othersThe concept of big data analysis, including what is big data, why big data is important, the application of big data in today's world as well as the different data analysis tools that you can useThe link between big data and machine learningThe different machine learning algorithms, including what machine-learning algorithms are and how and when the different learning algorithms are usedThe concept of artificial neural networks, including how they work, when to use neural networks and moreHow decision trees are used in machine learning, including what decision trees are (in respect to machine learning), how they work, how the decision tree is read, the different nodes in decision trees and when to use themThe ins and outs ...