Python Machine Learning By Example. Build intelligent systems using Python, TensorFlow 2, PyTorch, and scikit-learn - Third Edition

Yuxi (Hayden) Liu

Python Machine Learning By Example. Implement machine learning algorithms and techniques to build intelligent systems - Second Edition

Yuxi (Hayden) Liu

Python Machine Learning By Example. Unlock machine learning best practices with real-world use cases - Fourth Edition

Yuxi (Hayden) Liu

Python Machine Learning Cookbook. Over 100 recipes to progress from smart data analytics to deep learning using real-world datasets - Second Edition

Giuseppe Ciaburro, Prateek Joshi

Python. Machine learning i deep learning. Biblioteki scikit-learn i TensorFlow 2. Wydanie III

Sebastian Raschka, Vahid Mirjalili

Python Machine Learning. Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow - Second Edition

Sebastian Raschka, Vahid Mirjalili

Python Machine Learning. Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2 - Third Edition

Sebastian Raschka, Vahid Mirjalili

Python Natural Language Processing Cookbook. Over 60 recipes for building powerful NLP solutions using Python and LLM libraries - Second Edition

Zhenya Antić, Saurabh Chakravarty

Python Reinforcement Learning Projects. Eight hands-on projects exploring reinforcement learning algorithms using TensorFlow

Sean Saito, Yang Wenzhuo, Rajalingappaa Shanmugamani

Python. Uczenie maszynowe

Sebastian Raschka

Python. Uczenie maszynowe. Wydanie II

Sebastian Raschka, Vahid Mirjalili

Python w uczeniu maszynowym

Matthew Kirk

PyTorch Deep Learning Hands-On. Build CNNs, RNNs, GANs, reinforcement learning, and more, quickly and easily

Sherin Thomas, Sudhanshu Passi

Quantum Machine Learning and Optimisation in Finance. On the Road to Quantum Advantage

Antoine Jacquier, Oleksiy Kondratyev, Alexander Lipton, Marcos López de Prado

R Deep Learning Cookbook. Solve complex neural net problems with TensorFlow, H2O and MXNet

PKS Prakash, Achyutuni Sri Krishna Rao

R Deep Learning Essentials. A step-by-step guide to building deep learning models using TensorFlow, Keras, and MXNet - Second Edition

Mark Hodnett, Joshua F. Wiley

R Deep Learning Projects. Master the techniques to design and develop neural network models in R

Yuxi (Hayden) Liu, Pablo Maldonado

R Machine Learning Essentials. Gain quick access to the machine learning concepts and practical applications using the R development environment

Michele Usuelli

R Machine Learning Projects. Implement supervised, unsupervised, and reinforcement learning techniques using R 3.5

Dr. Sunil Kumar Chinnamgari

R Programming Fundamentals. Deal with data using various modeling techniques

Kaelen Medeiros

Recurrent Neural Networks with Python Quick Start Guide. Sequential learning and language modeling with TensorFlow

Simeon Kostadinov

Reinforcement Learning with TensorFlow. A beginner's guide to designing self-learning systems with TensorFlow and OpenAI Gym

Sayon Dutta

Reproducible Data Science with Pachyderm. Learn how to build version-controlled, end-to-end data pipelines using Pachyderm 2.0

Svetlana Karslioglu

Scala for Machine Learning. Leverage Scala and Machine Learning to construct and study systems that can learn from data

Patrick R. Nicolas