Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms

Buy

With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field.

Companies such as Google, Microsoft, and Facebook are actively growing in-house deep-learning teams. For the rest of us, however, deep learning is still a pretty complex and difficult subject to grasp. If you’re familiar with Python, and have a background in calculus, along with a basic understanding of machine learning, this book will get you started.

  • Examine the foundations of machine learning and neural networks
  • Learn how to train feed-forward neural networks
  • Use TensorFlow to implement your first neural network
  • Manage problems that arise as you begin to make networks deeper
  • Build neural networks that analyze complex images
  • Perform effective dimensionality reduction using autoencoders
  • Dive deep into sequence analysis to examine language
  • Understand the fundamentals of reinforcement learning
(HTML tags aren't allowed.)

Practical Statistics for Data Scientists: 50 Essential Concepts
Practical Statistics for Data Scientists: 50 Essential Concepts

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their...

Practical Machine Learning
Practical Machine Learning

About This Book

  • Fully-coded working examples using a wide range of machine learning libraries and tools, including Python, R, Julia, and Spark
  • Comprehensive practical solutions taking you into the future of machine learning
  • Go a step further and integrate your machine learning projects with...
Coding Projects in Python
Coding Projects in Python

Using fun graphics and easy-to-follow instructions, this straightforward, this visual guide shows young learners how to build their own computer projects using Python, an easy yet powerful free programming language available for download.

Perfect for kids ages 10 and over who are ready to take a second step after Scratch, Coding...


Introduction to Machine Learning with Python: A Guide for Data Scientists
Introduction to Machine Learning with Python: A Guide for Data Scientists

Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available...

Advanced Microservices: A Hands-on Approach to Microservice Infrastructure and Tooling
Advanced Microservices: A Hands-on Approach to Microservice Infrastructure and Tooling

Use the many types of tools required to navigate and maintain a microservice ecosystem. This book examines what is normally a complex system of interconnected services and clarifies them one at a time, first examining theoretical requirements then looking at concrete tools, configuration, and workflows.

Building out these systems...

The Self-Taught Programmer: The Definitive Guide to Programming Professionally
The Self-Taught Programmer: The Definitive Guide to Programming Professionally

I am a self-taught programmer. After a year of self-study, I learned to program well enough to land a job as a software engineer II at eBay. Once I got there, I realized I was severely under-prepared. I was overwhelmed by the amount of things I needed to know but hadn't learned yet. My journey learning to program, and my experience at my...

©2017 LearnIT (support@pdfchm.net) - Privacy Policy