Python Deep Learning Solutions [Video]

More Information
Learn
  • Implement different neural network models in Python
  • Select the best Python framework for Deep Learning such as PyTorch, Tensorflow, MXNet, and Keras
  • Boost learning performance by applying tips and tricks related to neural network internals 
  • Consolidate machine learning principles and apply them in the Deep Learning field
  • Reuse Python code snippets and adapt them to everyday problems
  • Evaluate the cost/benefits and performance implication of each discussed solution
About

Deep Learning is revolutionizing a wide range of industries. For many applications, Deep Learning has been proven to outperform humans by making faster and more accurate predictions. This course provides a top-down and bottom-up approach to demonstrating Deep Learning solutions to real-world problems in different areas.

These applications include Computer Vision, Generative Adversarial Networks, and time series. This course presents technical solutions to the issues presented, along with a detailed explanation of the solutions.

Furthermore, it provides a discussion on the corresponding pros and cons of implementing the proposed solution using a popular framework such as TensorFlow, PyTorch, and Keras. The course includes solutions that are related to the basic concepts of neural networks; all techniques, as well as classical network topologies, are covered. The main purpose of this video course is to provide Python programmers with a detailed list of solutions so they can apply Deep Learning to common and not-so-common scenarios.

Style and Approach

This video course is a unique blend of independent solutions arranged in the most logical manner.

Features
  • Practical video on training different neural network models and fine-tuning them for optimal performance
  • Use Python frameworks such as TensorFlow, Caffe, Keras, and Theano for Natural Language Processing, Computer Vision, and more
  • A hands-on guide covering the common (and not so common) problems in Deep Learning using Python
Course Length 1 hour 45 minutes
ISBN 9781789531602
Date Of Publication 26 Jun 2018

Authors

Indra den Bakker

Indra den Bakker is an experienced Deep Learning engineer and mentor. He is the founder of 23insights (part of NVIDIA's Inception program), a machine learning start-up building solutions that transform the world's most important industries. For Udacity, he mentors students pursuing a Nanodegree in Deep Learning and related fields, and he is also responsible for reviewing student projects. Indra has a background in computational intelligence and worked for several years as a data scientist for IPG Mediabrands and Screen6 before founding 23insights.