Sudharsan Ravichandiran is a data scientist and artificial intelligence enthusiast. He holds a Bachelors in Information Technology from Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning including natural language processing and computer vision. He is an open-source contributor and loves answering questions on Stack Overflow.
Sudharsan Ravichandiran - ebooki
Tytuły autora: Sudharsan Ravichandiran dostępne w księgarni Helion
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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.
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Getting Started with Google BERT. Build and train state-of-the-art natural language processing models using BERT Getting Started with Google BERT. Build and train state-of-the-art natural language processing models using BERT
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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.
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Deep Reinforcement Learning with Python. Master classic RL, deep RL, distributional RL, inverse RL, and more with OpenAI Gym and TensorFlow - Second Edition Deep Reinforcement Learning with Python. Master classic RL, deep RL, distributional RL, inverse RL, and more with OpenAI Gym and TensorFlow - Second Edition
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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.
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Hands-On Deep Learning Algorithms with Python. Master deep learning algorithms with extensive math by implementing them using TensorFlow Hands-On Deep Learning Algorithms with Python. Master deep learning algorithms with extensive math by implementing them using TensorFlow
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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.
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Python Reinforcement Learning. Solve complex real-world problems by mastering reinforcement learning algorithms using OpenAI Gym and TensorFlow Python Reinforcement Learning. Solve complex real-world problems by mastering reinforcement learning algorithms using OpenAI Gym and TensorFlow
Sudharsan Ravichandiran, Sean Saito, Rajalingappaa Shanmugamani, Yang Wenzhuo
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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.
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Hands-On Meta Learning with Python. Meta learning using one-shot learning, MAML, Reptile, and Meta-SGD with TensorFlow Hands-On Meta Learning with Python. Meta learning using one-shot learning, MAML, Reptile, and Meta-SGD with TensorFlow
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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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Hands-On Reinforcement Learning with Python. Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow Hands-On Reinforcement Learning with Python. Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow
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