Uczenie maszynowe

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

Hands-On Music Generation with Magenta. Explore the role of deep learning in music generation and assisted music composition

Alexandre DuBreuil

Hands-On Natural Language Processing with Python. A practical guide to applying deep learning architectures to your NLP applications

Rajesh Arumugam, Rajalingappaa Shanmugamani

Hands-On Neural Network Programming with C#. Add powerful neural network capabilities to your C# enterprise applications

Matt Cole

Hands-On Neural Networks with Keras. Design and create neural networks using deep learning and artificial intelligence principles

Niloy Purkait

Hands-On One-shot Learning with Python. Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch

Shruti Jadon, Ankush Garg

Hands-On Python Deep Learning for the Web. Integrating neural network architectures to build smart web apps with Flask, Django, and TensorFlow

Anubhav Singh, Sayak Paul

Hands-On Q-Learning with Python. Practical Q-learning with OpenAI Gym, Keras, and TensorFlow

Nazia Habib

Hands-On Reinforcement Learning with Python. Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow

Sudharsan Ravichandiran

Hands-On Simulation Modeling with Python. Develop simulation models to get accurate results and enhance decision-making processes

Giuseppe Ciaburro

Hands-On Transfer Learning with Python. Implement advanced deep learning and neural network models using TensorFlow and Keras

Dipanjan Sarkar, Raghav Bali, Tamoghna Ghosh

Hands-On Unsupervised Learning with Python. Implement machine learning and deep learning models using Scikit-Learn, TensorFlow, and more

Giuseppe Bonaccorso

IBM Cloud Pak for Data. An enterprise platform to operationalize data, analytics, and AI

Hemanth Manda, Sriram Srinivasan, Deepak Rangarao

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

James D. Miller

Inteligentna sieć. Algorytmy przyszłości. Wydanie II

Douglas McIlwraith, Haralambos Marmanis, Dmitry Babenko

Intelligent Projects Using Python. 9 real-world AI projects leveraging machine learning and deep learning with TensorFlow and Keras

Santanu Pattanayak, Manohar Swamynathan

Intelligent Workloads at the Edge. Deliver cyber-physical outcomes with data and machine learning using AWS IoT Greengrass

Indraneel (Neel) Mitra, Ryan Burke

Interpretable Machine Learning with Python. Build explainable, fair, and robust high-performance models with hands-on, real-world examples - Second Edition

Serg Masís, Aleksander Molak, Denis Rothman