Python Deep Learning Solutions

Video Description

Over 20 practical videos on neural network modeling, reinforcement learning, and transfer learning using Python

About This Video

  • 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

In Detail

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.

All the code and supporting files for this course are available on Github at

Product Information

  • Title: Python Deep Learning Solutions
  • Author(s): Indra den Bakker
  • Release date: June 2018
  • Publisher(s): Packt Publishing
  • ISBN: 9781789531602