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  • - Build and train state-of-the-art natural language processing models using BERT
    av Sudharsan Ravichandiran
    523,-

    Getting Started with Google BERT will help you become well-versed with the BERT model from scratch and learn how to create interesting NLP applications. You'll understand several variants of BERT such as ALBERT, RoBERTa, DistilBERT, ELECTRA, VideoBERT, and many others in detail.

  • - Master classic RL, deep RL, distributional RL, inverse RL, and more with OpenAI Gym and TensorFlow, 2nd Edition
    av Sudharsan Ravichandiran
    541,-

    Deep Reinforcement Learning with Python - Second Edition will help you learn reinforcement learning algorithms, techniques and architectures - including deep reinforcement learning - from scratch. This new edition is an extensive update of the original, reflecting the state-of-the-art latest thinking in reinforcement learning.

  • - Solve complex real-world problems by mastering reinforcement learning algorithms using OpenAI Gym and TensorFlow
    av Rajalingappaa Shanmugamani, Sudharsan Ravichandiran, Sean Saito & m.fl.
    595,-

    Reinforcement learning and deep reinforcement learning are the trending and most promising branches of artificial intelligence. This Learning Path will enable you to master not only the basic reinforcement learning algorithms but also the advanced deep reinforcement learning algorithms and their limitations.

  • - Master deep learning algorithms with extensive math by implementing them using TensorFlow
    av Sudharsan Ravichandiran
    479,-

    This book introduces basic-to-advanced deep learning algorithms used in a production environment by AI researchers and principal data scientists; it explains algorithms intuitively, including the underlying math, and shows how to implement them using popular Python-based deep learning libraries such as TensorFlow.

  • - Meta learning using one-shot learning, MAML, Reptile, and Meta-SGD with TensorFlow
    av Sudharsan Ravichandiran
    523,-

    This hands-on guide for meta learning starts with exploring the principles, algorithms, and implementations of Meta learning with Tensorflow, Keras, and Python. Once it sets the foundation of "learning to learn", the book will help you implement your meta learning algorithms from scratch.

  • - Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow
    av Sudharsan Ravichandiran
    479,-

    Reinforcement learning is a self-evolving type of machine learning that takes us closer to achieving true artificial intelligence. This easy-to-follow guide explains everything from scratch using rich examples written in Python.

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