Advanced Machine Learning: Mastering Level Learning with Python

Want to Become a Guru of Machine Learning? Have you just completed the book "An Intermediate's Guide to Machine Learning" Now it's time to go in Advanced Machine Learning Knowledge Advanced Machine Learning Hello! Welcome to this guide to advanced machine learning using Python & R. It's possible that you've picked this up with some initial interest, but aren't quite sure what to expect. In a nutshell, there has never been a more exciting time to learn and use machine learning techniques, and working in the field is only getting more rewarding. If you want to get up-to-speed with some of the more advanced Machine Learning techniques and gain experience using them to solve challenging problems, this is a good book for you! You will learn: Unsupervised Machine Learning Artificial Neural Networks & Convolutional Neural Networks Deep Learning Machine Learning with TensorFlow Pattern Recognition, Face Recognition & Image Recognition Python & R Codes for Machine Learning Algorithms Description: Interested in the field of Advanced Machine Learning? Then this book is for you! The rapid development of machine learning applications is fueled by an ongoing struggle to continually innovate, playing out at an array of research labs. The techniques developed by these pioneers are seeding new application areas and experiencing growing public awareness. While some of the innovations sought in AI and applied machine learning are still elusively far from readiness, others are a reality. Self-driving cars, sophisticated image recognition and altering capability, ever-greater strides in genetics research, and perhaps most pervasively of all, increasingly tailored content in our digital stores, e-mail inboxes, and online lives. Download your copy now so you can get started on what is promising to be a most amazing future.

• | Author: Thomas Farth
• | Publisher: Independently published
• | Publication Date: Nov 20, 2018
• | Number of Pages: 85 pages
• | Language: English
• | Binding: Paperback
• | ISBN-10: 1790120527
• | ISBN-13: 9781790120529