Mastering Keras

Rating 4.55 out of 5 (21 ratings in Udemy)

What you'll learn

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 …

Rating 4.55 out of 5 (21 ratings in Udemy)

What you'll learn

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

Description

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.

About the Author

Mike Ashcroft, PhD, is a lecturer at Uppsala University in Sweden. He teaches Masters and PhD students Artificial Intelligence and Statistical Machine Learning. He has created and delivered courses for the European Data Science Academy, Future Learn/Open University, and Sichuan University. He has a deep knowledge of, and experience working with, Keras.

Besides his university work, he has worked intensively with industrial applications of Artificial Intelligence and machine learning—both with startups (some of which he has founded) and, as a consultant, established companies and government agencies including SKF, the Swedish Defence Research Institute, and The Economist.

He is always interested in combining a deep understanding of how these fascinating techniques work with their practical applications. Mike brings to his courses a unique mixture of academic knowledge, industrial experience, and basic curiosity.

Duration 5 Hours 58 Minutes

Paid

Self paced

Intermediate Level

English (US)

105

Rating 4.55 out of 5 (21 ratings in Udemy)

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