Cut through the noise and get real results with a step-by-step approach to understanding deep learning with Keras programming

Key FeaturesIdeal for those getting started with Keras for the first timeA step-by-step Keras tutorial with exercises and activities that help build key skillsStructured to let you progress at your own pace, on your own termsUse your physical print copy to redeem free access to the online interactive editionBook Description

You already know that you want to learn Keras, and a smarter way to learn is to learn by doing. The Deep Learning with Keras Workshop focuses on building up your practical skills so that you can develop artificial intelligence applications or build machine learning models with Keras. You'll learn from real examples that lead to real results.

Throughout The Deep Learning with Keras Workshop, you'll take an engaging step-by-step approach to understand Keras. You won't have to sit through any unnecessary theory. If you're short on time you can jump into a single exercise each day or spend an entire weekend tinkering with your own neural networks. It's your choice. Learning on your terms, you'll build up and reinforce key skills in a way that feels rewarding.

Every physical print copy of The Deep Learning with Keras Workshop unlocks access to the interactive edition. With videos detailing all exercises and activities, you'll always have a guided solution. You can also benchmark yourself against assessments, track progress, and receive content updates. You'll even earn a secure credential that you can share and verify online upon completion. It's a premium learning experience that's included with your printed copy. To redeem, follow the instructions located at the start of your book.

Fast-paced and direct, The Deep Learning with Keras Workshop is the ideal companion for those who are just getting started with Keras. You'll build and iterate on your code like a software developer, learning along the way. This process means that you'll find that your new skills stick, embedded as best practice. A solid foundation for the years ahead.

What you will learnGain insight into the fundamental concepts of neural networksLearn to think like a data scientist and understand the difference between machine learning and deep learningDiscover various techniques to evaluate, tweak, and improve your modelsExplore different techniques to manipulate your dataExplore alternative techniques to verify the accuracy of your modelWho this book is for

Our goal at Packt is to help you be successful, in whatever it is that you choose to do. The Deep Learning with Keras Workshop is an ideal tutorial for the programmer who is getting started with Keras and deep learning. Pick up a Workshop today and let Packt help you develop skills that stick with you for life.

Matthew Moocarme is a director and senior data scientist in Viacom’s advertising science team. As a data scientist at Viacom, he designs data-driven solutions to help Viacom gain insights, streamline workflows, and solve complex problems using data science and machine learning. Matthew lives in New York City and outside of work enjoys combining deep learning with music theory. He is a classically-trained physicist, holding a Ph.D. in physics from The Graduate Center of CUNY and is an active artificial intelligence developer, researcher, practitioner, and educator. Mahla Abdolahnejad is a Ph.D. candidate in systems and computer engineering with Carleton University, Canada. She also holds a bachelor's degree and a master's degree in biomedical engineering, which first exposed her to the field of artificial intelligence and artificial neural networks, in particular. Her Ph.D. research is focused on deep unsupervised learning for computer vision applications. She is particularly interested in exploring the differences between a human's way of learning from the visual world and a machine's way of learning from the visual world, and how to push machine learning algorithms toward learning and thinking like humans. Ritesh Bhagwat has a master's degree in applied mathematics with a specialization in computer science. He has over 14 years of experience in data-driven technologies and has led and been a part of complex projects ranging from data warehousing and business intelligence to machine learning and artificial intelligence. He has worked with top-tier global consulting firms as well as large multinational financial institutions. Currently, he works as a data scientist. Besides work, he enjoys playing and watching cricket and loves to travel. He is also deeply interested in Bayesian statistics.