Title: Keras Deep Learning Cookbook: Over 30 recipes for implementing deep neural networks in Python, Author: Rajdeep Dua
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Title: Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits: A practical guide to implementing supervised and unsupervised machine learning algorithms in Python, Author: Tarek Amr
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Title: Quantum Computing and Blockchain in Business: Exploring the applications, challenges, and collision of quantum computing and blockchain, Author: Arunkumar Krishnakumar
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Title: Hands-On Neural Networks with TensorFlow 2.0: Understand TensorFlow, from static graph to eager execution, and design neural networks, Author: Paolo Galeone
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Title: PyTorch 1.x Reinforcement Learning Cookbook: Over 60 recipes to design, develop, and deploy self-learning AI models using Python, Author: Yuxi (Hayden) Liu
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Title: Cleaning Data for Effective Data Science: Doing the other 80% of the work with Python, R, and command-line tools, Author: David Mertz
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Title: Hands-On Reinforcement Learning for Games: Implementing self-learning agents in games using artificial intelligence techniques, Author: Micheal Lanham
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Title: Mastering Machine Learning with R: Advanced machine learning techniques for building smart applications with R 3.5, Author: Cory Lesmeister
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Title: Mastering Machine Learning for Penetration Testing: Develop an extensive skill set to break self-learning systems using Python, Author: Chiheb Chebbi
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Title: Hands-On Neuroevolution with Python: Build high-performing artificial neural network architectures using neuroevolution-based algorithms, Author: Iaroslav Omelianenko
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Title: Hands-On Artificial Intelligence on Amazon Web Services: Decrease the time to market for AI and ML applications with the power of AWS, Author: Subhashini Tripuraneni
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Title: Machine Learning with R, Author: Brett Lantz
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Title: Mastering Machine Learning Algorithms: Expert techniques to implement popular machine learning algorithms and fine-tune your models, Author: Giuseppe Bonaccorso
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Title: Python Deep Learning Cookbook: Solve different problems in modelling deep neural networks using Python, Tensorflow, and Keras with this practical guide, Author: Indra den Bakker
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Title: Deep Reinforcement Learning with Python: Master classic RL, deep RL, distributional RL, inverse RL, and more with OpenAI Gym and TensorFlow, Author: Sudharsan Ravichandiran
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Title: Hands-On Graph Neural Networks Using Python: Practical techniques and architectures for building powerful graph and deep learning apps with PyTorch, Author: Maxime Labonne
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Title: Deep Learning with TensorFlow and Keras: Build and deploy supervised, unsupervised, deep, and reinforcement learning models, Author: Amita Kapoor
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Title: Scala for Machine Learning, Author: Patrick R. Nicolas
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Title: Write Great Code, Volume 1, 2nd Edition: Understanding the Machine, Author: Randall Hyde
Title: Arduino Wearable Projects, Author: Tony Olsson
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