Machine Learning for Developers

▶About This Book
Today, a network with hundreds of millions of degrees of freedom can be assembled in minutes, trained in hours, and put into production in a few days, (obviously, if you know the right technologies to so).

This is one of the reasons why most of the radical advancements in
computer vision, language understanding, and pattern recognition in general are being driven specifically by different flavors of neural networks that have been proposed recently.

This exponentially growing set of knowledge, techniques, and programming libraries makes most classical texts on the subject obsolete, at least for the deployment of fast and practical applications.

For this reason, a book like this can be celebrated as a quick and to-the-point text that provides all the materials required to successfully implement and understand a machine learning application in a single reading. In this book, you will find:

1. The fundamentals of machine learning tasks (classification, clustering, regression, and data reduction), together with a quick, yet comprehensive introduction to the mathematical and statistical foundations of the subject.
2. A more detailed presentation of Neural Networks as a learning model, together with basics of the training algorithms, convergence crite0ria, and the evaluation of results.
3. An introduction the most advanced learning models using more elaborate
networks, including convolutional, recurrent, and adversarial networks. Each of the models is analyzed thoroughly, both in theoretical and in practical
considerations.
4. A comprehensive guide to open source software that, together with the previous material, allows the reader to put the concepts into practice very quickly.


This book is highly recommended for practitioners in academia who feel their expertise is becoming outdated, for developers who need to deploy sophisticated machine learning features in business applications, and for anyone willing to gain a broad and practical understanding of machine learning. The author transmits his vast experience in the subject in a very clear and systematic manner, making the book easy to follow and put into
practice.

▶Key Features
⦁ Learn to develop efficient and intelligent applications by leveraging the power of Machine Learning
⦁ A highly practical guide explaining the concepts of problem solving in the easiest possible manner
⦁ Implement Machine Learning in the most practical way

▶What You Will Learn
⦁ Learn the math and mechanics of Machine Learning via a developer-friendly approach
⦁ Get to grips with widely used Machine Learning algorithms/techniques and how to use them to solve real problems
⦁ Get a feel for advanced concepts, using popular programming frameworks.
⦁ Prepare yourself and other developers for working in the new ubiquitous field of Machine Learning
⦁ Get an overview of the most well known and powerful tools, to solve computing problems using Machine Learning.
⦁ Get an intuitive and down-to-earth introduction to current Machine Learning areas, and apply these concepts on interesting and cutting-edge problems.