Packt – Mastering Keras

Packt – Mastering Keras-XQZT
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Category: Tutorial

Explore powerful deep learning techniques using Keras
Successful data scientists need to be able to work with the most powerful tools to solve the most challenging problems. As deep learning becomes ever more entrenched as the gold-standard tool for a wide variety of advanced data analytics and Artificial Intelligence problems, it is essential for you as a data scientist or analyst to be comfortable wielding these powerful techniques on an ever-expanding array of problems.

TensorFlow (and its easy-to-learn deep learning wrapper Keras) have become game-changers in permitting simple implementations of the most complex of deep learning techniques.

In this course, we teach you to go beyond your working knowledge of Keras, begin to wield its full power, and unleash the amazing potential of advanced deep learning on your data science problems. You’ll learn to design and train deep learning models for synthetic data generation, object detection, one-shot learning, and much more.

By the end of this course, you will be able to implement many advanced deep learning modelling algorithms and adapt them to your own purposes. Perhaps the next great breakthrough will come from you?

Please note that familiarity with machine learning and deep learning approaches, together with practical experience with Keras and Python programming, are assumed for taking this course.

All related code files are placed on a GitHub repository at:

Upgrade your mastery of deep learning and apply advanced techniques to a wide variety of real-world problems
Master the potential of the world’s most popular and powerful deep learning tool and its functional API
Discover the advanced potentialities of deep learning with this engaging and jargon-free course delivered by a leading globally-recognized academic

Use the powerfully functional Keras API to design and implement advanced deep learning techniques
Design and implement advanced Convolutional Neural Networks for powerful image classification
Design and implement object detection networks to identify objects present in images and their location
Work with deep generative neural networks for synthetic data generation and semi-supervised learning
Develop a stable deep reinforcement-learning system and learn to make optimal decisions via feedback from their environment
Implement deep one-shot learning systems that can classify new instances of a class after a single exposure to such an object

Course Length 5 hours 17 minutes
ISBN 9781838823863
Date Of Publication 10 Feb 2020

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