Keras Tips, Tricks, and Techniques

Machine learning and deep learning allow us to interpret data structures and fit that data into models to identify patterns and make predictions. Keras makes this easier with its huge set of libraries that can be easily used for machine learning.
Designed for those with some existing Python and Keras skills and familiarity with machine learning principles, this course will enable you to enrich your skills by covering a number of more advanced applications. In this course, you will get hands-on experience in solving real problems by implementing cutting-edge techniques to significantly boost your Keras skills and, as a consequence, expand your ability to apply Keras to real-world problems. Throughout the course, you will work on real datasets to increase your expertise and keep adding new tools to your Keras toolbox.
By the end of this course, you will learn various tips, tricks, and techniques to upgrade your machine learning and deep learning algorithm knowledge, as well as how to build efficient models with Keras.
By the end of this course, you will have learned various tips, tricks, and techniques to upgrade your machine learning and deep learning algorithm knowledge; you will also be able to build efficient models with Keras.
About the Author
John de Havilland has worked in the field of software engineering for over a decade, working on a large scale, distributed systems across a variety of industries. He has spent the last several years focused on Big Data and Artificial Intelligence, helping customers build and implement advanced data and AI platforms in the cloud. He currently works as a Customer Success Director at Microsoft leading a team of cloud solution architects, advising and guiding top clients on advanced cloud-based solutions to solve their most challenging business needs.