Description
This course is all about some of the most significant applications of deep learning and how to implement them in TensorFlow. You will learn how to build models to solve problems in different domains such as computer vision, natural language processing, reinforcement learning, and finance. This course presents you with easy-to-follow recipes to show the use of advanced deep learning techniques and their implementation in TensorFlow. After taking this tutorial, you will be able to start building advanced deep learning models with TensorFlow for applications with a wide range of fields.
What You Will Learn:
- Implement convolutional neural networks and use them for computer vision
- Build recurrent neural network models and use them for natural language processing tasks
- Apply foundational models in reinforcement learning
- Use deep learning models implemented in TensorFlow to solve problems in many domains
- Start building your deep learning applications
All the code and supporting files for this course are available on Github at https://github.com/PacktPublishing/-TensorFlow-1.X-Deep-Learning-Recipes-for-Artificial-Intelligence-Applications-v-.
Example Curriculum
CONVOLUTIONAL NEURAL NETWORKS FOR COMPUTER VISION
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APPLICATIONS OF RECURRENT NEURAL NETWORKS
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APPLICATION OF DEEP LEARNING TO AI PROBLEMS
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INTRODUCTION TO REINFORCEMENT LEARNING
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