Hands-On Image Processing with Python. Expert techniques for advanced image analysis and effective interpretation of image data

Sandipan Dey

Hands-On Intelligent Agents with OpenAI Gym. Your guide to developing AI agents using deep reinforcement learning

Palanisamy P

Hands-On Java Deep Learning for Computer Vision. Implement machine learning and neural network methodologies to perform computer vision-related tasks

Klevis Ramo

Hands-On Machine Learning for Algorithmic Trading. Design and implement investment strategies based on smart algorithms that learn from data using Python

Stefan Jansen

Hands-On Machine Learning for Cybersecurity. Safeguard your system by making your machines intelligent using the Python ecosystem

Soma Halder, Sinan Ozdemir

Hands-On Machine Learning with Azure. Build powerful models with cognitive machine learning and artificial intelligence

Thomas K Abraham, Parashar Shah, Jen Stirrup, Lauri Lehman, ...

Hands-On Machine Learning with C++. Build, train, and deploy end-to-end machine learning and deep learning pipelines

Kirill Kolodiazhnyi

Hands-On Machine Learning with IBM Watson. Leverage IBM Watson to implement machine learning techniques and algorithms using Python

James D. Miller

Hands-on Machine Learning with JavaScript. Solve complex computational web problems using machine learning

Burak Kanber

Hands-On Machine Learning with Microsoft Excel 2019. Build complete data analysis flows, from data collection to visualization

Julio Cesar Rodriguez Martino

Hands-On Machine Learning with ML.NET. Getting started with Microsoft ML.NET to implement popular machine learning algorithms in C#

Jarred Capellman

Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits. A practical guide to implementing supervised and unsupervised machine learning algorithms in Python

Tarek Amr

Hands-On Machine Learning with TensorFlow.js. A guide to building ML applications integrated with web technology using the TensorFlow.js library

Kai Sasaki

Hands-On Markov Models with Python. Implement probabilistic models for learning complex data sequences using the Python ecosystem

Ankur Ankan, Abinash Panda

Hands-On Mathematics for Deep Learning. Build a solid mathematical foundation for training efficient deep neural networks

Jay Dawani

Hands-On Meta Learning with Python. Meta learning using one-shot learning, MAML, Reptile, and Meta-SGD with TensorFlow

Sudharsan Ravichandiran