The flexible architecture of TensorFlow allows you to create and deploy deep learning and deep reinforcement learning models for building intelligent, real-world applications. TensorFlow facilitates AI to build and train systems, in particular, neural networks.
This comprehensive 2-in-1 course is a hands-on approach to problem-solving. Gain practical knowledge by coding TensorFlow models to solve real-life problems such as gesture or voice recognition. You’ll also learn to deploy TensorFlow models on mobile devices.
Contents and Overview
This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.
The first course, Hands-on Artificial Intelligence with TensorFlow, covers a practical approach to deep learning and deep reinforcement learning for building real-world applications using TensorFlow. This course will teach you how to combine the power of Artificial Intelligence and TensorFlow to develop some exciting applications for the real world. You will then be taken through techniques such as reinforcement learning, heuristic searches, neural networks, Computer Vision, OpenAI Gym, and more in different stages of your application.
The second course, Hands-on TensorFlow Lite for Intelligent Mobile Apps, covers application of Machine Learning models in real-time in mobile devices with the new and powerful TensorFlow Lite. This course will teach you how to solve real-life problems related to Artificial Intelligence—such as image, text, and voice recognition—by developing models in TensorFlow to make your applications really smart. You will understand what Machine Learning can do for you and your mobile applications in the most efficient way. With the capabilities of TensorFlow Lite you will learn to improve the performance of your mobile application and make it smart.
By the end of the course, you’ll be able to implement AI in your mobile applications as well as build intelligent apps by leveraging the full potential of Artificial Intelligence with TensorFlow.
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