Programming Machine Learning

Programming Machine Learning
Author :
Publisher : Pragmatic Bookshelf
Total Pages : 437
Release :
ISBN-10 : 9781680507713
ISBN-13 : 1680507710
Rating : 4/5 (13 Downloads)

Book Synopsis Programming Machine Learning by : Paolo Perrotta

Download or read book Programming Machine Learning written by Paolo Perrotta and published by Pragmatic Bookshelf. This book was released on 2020-03-31 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: You've decided to tackle machine learning - because you're job hunting, embarking on a new project, or just think self-driving cars are cool. But where to start? It's easy to be intimidated, even as a software developer. The good news is that it doesn't have to be that hard. Master machine learning by writing code one line at a time, from simple learning programs all the way to a true deep learning system. Tackle the hard topics by breaking them down so they're easier to understand, and build your confidence by getting your hands dirty. Peel away the obscurities of machine learning, starting from scratch and going all the way to deep learning. Machine learning can be intimidating, with its reliance on math and algorithms that most programmers don't encounter in their regular work. Take a hands-on approach, writing the Python code yourself, without any libraries to obscure what's really going on. Iterate on your design, and add layers of complexity as you go. Build an image recognition application from scratch with supervised learning. Predict the future with linear regression. Dive into gradient descent, a fundamental algorithm that drives most of machine learning. Create perceptrons to classify data. Build neural networks to tackle more complex and sophisticated data sets. Train and refine those networks with backpropagation and batching. Layer the neural networks, eliminate overfitting, and add convolution to transform your neural network into a true deep learning system. Start from the beginning and code your way to machine learning mastery. What You Need: The examples in this book are written in Python, but don't worry if you don't know this language: you'll pick up all the Python you need very quickly. Apart from that, you'll only need your computer, and your code-adept brain.


Programming Machine Learning Related Books

Programming Machine Learning
Language: en
Pages: 437
Authors: Paolo Perrotta
Categories: Computers
Type: BOOK - Published: 2020-03-31 - Publisher: Pragmatic Bookshelf

DOWNLOAD EBOOK

You've decided to tackle machine learning - because you're job hunting, embarking on a new project, or just think self-driving cars are cool. But where to start
Genetic Algorithms and Machine Learning for Programmers
Language: en
Pages: 307
Authors: Frances Buontempo
Categories: Computers
Type: BOOK - Published: 2019-01-23 - Publisher: Pragmatic Bookshelf

DOWNLOAD EBOOK

Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to Machine Learning. Now you can create your own gene
Deep Learning for Coders with fastai and PyTorch
Language: en
Pages: 624
Authors: Jeremy Howard
Categories: Computers
Type: BOOK - Published: 2020-06-29 - Publisher: O'Reilly Media

DOWNLOAD EBOOK

Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with
Mathematics and Programming for Machine Learning with R
Language: en
Pages: 408
Authors: William B. Claster
Categories: Computers
Type: BOOK - Published: 2020-10-26 - Publisher: CRC Press

DOWNLOAD EBOOK

Based on the author’s experience in teaching data science for more than 10 years, Mathematics and Programming for Machine Learning with R: From the Ground Up
AI and Machine Learning for Coders
Language: en
Pages: 393
Authors: Laurence Moroney
Categories: Computers
Type: BOOK - Published: 2020-10-01 - Publisher: O'Reilly Media

DOWNLOAD EBOOK

If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI