Torch: Getting started with Machine and Deep Learning Training Course

Course Code

Torch

Duration

21 hours (usually 3 days including breaks)

Requirements

  • Programming experience in any language
  • A general familiarity with C/C++ helps
  • An interest in Artificial Intelligence (AI)

Overview

Torch is an open source machine learning library and a scientific computing framework based on the Lua programming language. It provides a development environment for numerics, machine learning, and computer vision, with a particular emphasis on deep learning and convolutional nets. It is one of the fastest and most flexible frameworks for Machine and Deep Learning and is used by companies such as Facebook, Google, Twitter, NVIDIA, AMD, Intel, and many others.

In this course we cover the principles of Torch, its unique features, and how it can be applied in real-world applications. We step through numerous hands-on exercises all throughout, demonstrating and practicing the concepts learned.

By the end of the course, participants will have a thorough understanding of Torch's underlying features and capabilities as well as its role and contribution within the AI space compared to other frameworks and libraries. Participants will have also received the necessary practice to implement Torch in their own projects.

Audience
    Software developers and programmers wishing to enable Machine and Deep Learning within their applications

Format of the course
    Overview of Machine and Deep Learning
    In-class coding and integration exercises
    Test questions sprinkled along the way to check understanding

Course Outline

Introduction to Torch
    Like NumPy but with CPU and GPU implementation
    Torch's usage in machine learning, computer vision, signal processing, parallel processing, image, video, audio and networking

Installing Torch
    Linux, Windows, Mac
    Bitmapi and Docker

Installing Torch packages
    Using the LuaRocks package manager

Choosing an IDE for Torch
    ZeroBrane Studio
    Eclipse plugin for Lua

Working with the Lua scripting language and LuaJIT
    Lua's integration with C/C++
    Lua syntax: datatypes, loops and conditionals, functions, functions, tables, and file i/o.
    Object orientation and serialization in Torch
    Coding exercise

Loading a dataset in Torch
    MNIST
    CIFAR-10, CIFAR-100
    Imagenet

Machine Learning in Torch
    Deep Learning
        Manual feature extraction vs convolutional networks
    Supervised and Unsupervised Learning
        Building a neural network with Torch    
    N-dimensional arrays

Image analysis with Torch
    Image package
    The Tensor library

Working with the REPL interpreter

Working with databases

Networking and Torch

GPU support in Torch

Integrating Torch
    C, Python, and others

Embedding Torch
    iOS and Android

Other frameworks and libraries
    Facebook's optimized deep-learning modules and containers

Creating your own package

Testing and debugging

Releasing your application

The future of AI and Torch

Testimonials

★★★★★
★★★★★

Bookings, Prices and Enquiries

Guaranteed to run even with a single delegate!

Private Classroom

From £4350

Private Remote

From £3900 (97)

Public Classroom

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Course Discounts

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