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Hands-On Python Deep Learning [Video]

More Information
Learn
  • Implementing different neural network models in Python
  • Select the best Python framework for deep learning such as TensorFlow and Keras
  • Build Deep Neural Networks in the healthcare domain to address applications of deep learning in it
  • Apply deep learning techniques and generating production-quality visualizations
  • Practical ways in which deep learning techniques can be applied to develop solutions for image recognition
  • Explore face recognition with Deep Learning
  • Apply document characterization with Deep Learning
  • Work with dialog generation with Deep Learning
About

Deep learning is the next step to a more advanced implementation of machine learning. The course resolves the confusion between machine learning and deep learning by focusing only on deep learning concepts. Deep learning techniques are used in real-world scenarios such as image scanning, face detection, and many more. It is important to know deep learning algorithms as they are currently trending in sectors such as healthcare, finance, and many more. This hands-on course will help you tackle various issues that you come across while building your Deep Learning applications in the healthcare domain. Right from building your neural nets to reinforcement learning and working with different Deep Learning applications such as computer Vision and voice and image recognition, this course will be your guide in tackling different situations and issues and provide the end to end application of deep learning concepts in the healthcare domain. By the end of the course, you will be able to build neural networks and Deep learning models for your own projects.

The code bundle for this video course is available at - https://github.com/PacktPublishing/Hands-On-Python-Deep-Learning

Style and Approach

This course is a step-by-step structured video tutorial with practical examples and coding to provide solutions to Deep Learning problems in Python. The course's approach includes various sections, starting with the basic implementation and moving on to advanced levels; each section includes a challenging case study to boost your thinking ability.

Features
  • Apply Deep Learning techniques to develop solutions for a healthcare dataset
  • A hands-on guide covering common as well as not-so-common problems in deep learning using Python
  • Get started with Deep Learning and build complex models layer by layer, with increasing complexity, in no time.
Course Length 2 hours 37 minutes
ISBN9781788999380
Date Of Publication 31 Jan 2019

Authors

Radhika Datar

Radhika Datar has more than 5 years' experience in Software Development and Content Writing. She is well versed with frameworks such as Python, PHP, and Java and regularly provides training on them. She has been working with Educba and Eduonix as a Training Consultant since June 2016 and as an Academic writer with TutorialsPoint since Sept 2015. She is also the author of the TensorFlow Succinctly e-book for Syncfusion Publications.