By Gianmario Spacagna,Daniel Slater,Valentino Zocca,Peter Roelants

Key Features

  • Explore and create clever platforms utilizing state-of-the-art deep studying techniques
  • Implement deep studying algorithms and paintings with innovative libraries in Python
  • Get real-world examples and easy-to-follow tutorials on Theano, TensorFlow, H2O and more

Book Description

With an expanding curiosity in AI world wide, deep studying has attracted loads of public consciousness. each day, deep studying algorithms are used largely throughout various industries.

The publication provide you with all of the sensible details to be had at the topic, together with the easiest practices, utilizing real-world use instances. you are going to learn how to realize and extract details to extend predictive accuracy and optimize results.

Starting with a short recap of vital laptop studying strategies, the ebook will delve instantly into deep studying ideas utilizing Sci-kit study. relocating forward, you are going to learn how to use the newest open resource libraries similar to Theano, Keras, Google's TensorFlow, and H20. Use this consultant to discover the problems of development reputation, scaling facts with larger accuracy and discussing deep studying algorithms and techniques.

Whether you must dive deeper into Deep studying, or are looking to examine the best way to get extra out of this robust know-how, you’ll locate every little thing inside.

What you are going to learn

  • Get a pragmatic deep dive into deep studying algorithms
  • Explore deep studying extra with Theano, Caffe, Kera, and TensorFlow
  • Learn approximately of the main strong ideas on the center of many functional deep studying implementations: Auto-Encoders and constrained Boltzmann Machines
  • Dive into Deep trust Nets and Deep Neural Networks
  • Discover extra deep studying algorithms with Dropout and Convolutional Neural Networks
  • Get to grasp equipment recommendations so that you can use deep studying algorithms and libraries within the genuine world

Show description

Read or Download Python Deep Learning PDF

Similar machine theory books

Download e-book for iPad: Theory of Semi-Feasible Algorithms (Monographs in by Lane A. Hemaspaandra,Leen Torenvliet

The first target of this booklet is unifying and making extra commonly obtainable the colourful movement of analysis - spanning greater than 20 years - at the thought of semi-feasible algorithms. In doing so it demonstrates the richness inherent in valuable notions of complexity: working time, nonuniform complexity, lowness, and NP-hardness.

New PDF release: Ramsey Theory for Discrete Structures

This monograph covers essentially the most vital advancements in Ramsey concept from its beginnings within the early twentieth century through its many breakthroughs to contemporary very important advancements within the early twenty first century. The booklet first offers an in depth dialogue of the roots of Ramsey thought prior to providing a radical dialogue of the function of parameter units.

Download e-book for kindle: Combinatorial Image Analysis: 17th International Workshop, by Reneta P. Barneva,Bhargab B. Bhattacharya,Valentin E.

This quantity constitutes the refereed lawsuits of the17th foreign Workshop on Combinatorial snapshot research, IWCIA 2015, heldin Kolkata, India, in November 2015. The 24 revised complete papers and a pair of invited papers presentedwere rigorously reviewed and chosen from a number of submissions. The workshopprovides theoretical foundations and techniques for fixing difficulties from variousareas of human perform.

Get Hybride Optimierung für Dimensionsreduktion: Unüberwachte PDF

In der Arbeit von Daniel Lückehe wird ein neues hybrides Verfahren zur Dimensionsreduktion methodisch erarbeitet, analysiert und durch experimentelle exams mit vorhandenen Methoden verglichen. Hochdimensionale Daten, häufig zusammengefasst unter dem Begriff „Big Data“, liegen heutzutage in vielen Bereichen vor.

Additional info for Python Deep Learning

Sample text

Download PDF sample

Python Deep Learning by Gianmario Spacagna,Daniel Slater,Valentino Zocca,Peter Roelants


by Edward
4.3

Rated 4.84 of 5 – based on 29 votes