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Machine Learning Algorithms : Popular algorithms for data science and machine learning, 2nd Edition

Go Machine Learning Projects : Eight projects demonstrating end-to-end machine learning and predictive analytics applications in Go

Modern Computer Vision with PyTorch : A practical and comprehensive guide to understanding deep learning and multimodal models for real-world vision tasks

Machine Learning Engineering with Python : Manage the lifecycle of machine learning models using MLOps with practical examples

Practical Guide to Applied Conformal Prediction in Python : Learn and apply the best uncertainty frameworks to your industry applications

Keras 2.x Projects : 9 projects demonstrating faster experimentation of neural network and deep learning applications using Keras

Deep Reinforcement Learning with Python : Master classic RL, deep RL, distributional RL, inverse RL, and more with OpenAI Gym and TensorFlow, 2nd Edition

Mastering PyTorch : Build powerful neural network architectures using advanced PyTorch 1.x features

Hands-On Neuroevolution with Python : Build high-performing artificial neural network architectures using neuroevolution-based algorithms

Apache Spark Deep Learning Cookbook : Over 80 recipes that streamline deep learning in a distributed environment with Apache Spark

IBM Watson Projects : Eight exciting projects that put artificial intelligence into practice for optimal business performance

TensorFlow 2 Reinforcement Learning Cookbook : Over 50 recipes to help you build, train, and deploy learning agents for real-world applications

Mastering Computer Vision with TensorFlow 2.x : Build advanced computer vision applications using machine learning and deep learning techniques

Hands-On Ensemble Learning with R : A beginner's guide to combining the power of machine learning algorithms using ensemble techniques

Hands-On Image Generation with TensorFlow : A practical guide to generating images and videos using deep learning

Keras Reinforcement Learning Projects : 9 projects exploring popular reinforcement learning techniques to build self-learning agents

Modern Computer Vision with PyTorch : Explore deep learning concepts and implement over 50 real-world image applications

Hands-On Explainable AI (XAI) with Python : Interpret, visualize, explain, and integrate reliable AI for fair, secure, and trustworthy AI apps

Deep Learning for Time Series Cookbook : Use PyTorch and Python recipes for forecasting, classification, and anomaly detection

Hands-On Artificial Intelligence on Amazon Web Services : Decrease the time to market for AI and ML applications with the power of AWS

Mastering Reinforcement Learning with Python : Build next-generation, self-learning models using reinforcement learning techniques and best practices

Ensemble Machine Learning : A beginner's guide that combines powerful machine learning algorithms to build optimized models

Deep Reinforcement Learning Hands-On : A practical and easy-to-follow guide to RL from Q-learning and DQNs to PPO and RLHF

Mastering Machine Learning Algorithms : Expert techniques for implementing popular machine learning algorithms, fine-tuning your models, and understanding how they work, 2nd Edition

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