Data Science and Machine Learning are rare skills in high demand in the job market. This field with rather vague outlines requires multidisciplinary expertise. Mastering matrix calculus, probabilities, programming as well as the main ML algorithms require colossal work! No doubt, Machine Learning takes time. but, we all want “ shortcuts ” to put the
No doubt, Machine Learning takes time. but, we all want “ shortcuts ” to put the most effort into where it is needed. After all, who doesn’t like to see the fruits of their labor quickly?
Here is a brief selection of eight must-have Machine Learning books for “beginners”, to read and reread without moderation.
1. Introduction to Machine Learning, fourth edition (Adaptive Computation and Machine Learning series)
The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Therefore, Machine learning underlies such exciting new technologies as self-driving cars, speech recognition, and translation applications. This substantially revised fourth edition of a comprehensive, widely used machine learning textbook offers new coverage of recent advances in the field in both theory and practice, including developments in deep learning and neural networks.
In other words, Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and also, document classification.
by Oliver Theobald | January 1, 2018
Machine Learning for Absolute Beginners Second Edition has been written and designed for absolute beginners. In other words, 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, finally.
by | May 26, 2019
A fully self-contained introduction to machine learning. All that the reader requires is an understanding of the basics of matrix algebra and calculus.
In the same way, Machine Learning: An Applied Mathematics Introduction covers the essential mathematics behind all of the most important techniques.
by Ethem Mining | Mar 29, 2020
This is a comprehensive guide that explains in a simple way how to manage machine learning and AI. In the same way, the term Machine Learning refers to the capability of a machine to learn something without any pre-existing program. Additionally, automatic learning is a way to educate an algorithm to learn from various environmental situations.
by Richard S. Sutton, Andrew G. Barto | Nov 13, 2018
Reinforcement learning, one of the most active research areas in artificial intelligence. Also, it is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment.
Master the world of Python and machine learning with this incredible four-in-one bundle. Created with the beginner in mind, this powerful bundle delves into the fundamentals behind Python and machine learning. Additionally, from basic code and mathematical formulas to complex neural networks and ensemble modeling.
by Ekaba Bisong | Sep 28, 2019
Take a systematic approach to understand the fundamentals of machine learning and deep learning from the ground up and how they are applied in practice. Then, you will use this comprehensive guide for building and deploying learning models to address complex use cases while leveraging the computational resources of Google Cloud Platform.