📘Python Deep Learning: Exploring deep learning techniques, neural network architectures and GANs with PyTorch, Keras and TensorFlow

What you will learn
• Grasp mathematical theory behind neural networks and deep learning process.
• Investigate and resolve computer vision challenges using convolutional networks and capsule networks.
• Solve Generative tasks using Variational Autoencoders and Generative Adversarial Nets (GANs).
• Explore Reinforcement Learning and understand how agents behave in a complex environment.
• Implement complex natural language processing tasks using recurrent networks (LSTM, GRU), and attention models.

Who This Book Is For
This book is for Data Science practitioners, Machine Learning Engineers and Deep learning aspirants who have a basic foundation of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired

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