Generative Adversarial Networks Projects. Build next-generation generative models using TensorFlow and Keras

Kailash Ahirwar

Generatywne głębokie uczenie, wyd. II. Uczenie maszyn, jak malować, pisać, komponować i grać

David Foster

Getting Started with Amazon SageMaker Studio. Learn to build end-to-end machine learning projects in the SageMaker machine learning IDE

Michael Hsieh

Getting Started with Streamlit for Data Science. Create and deploy Streamlit web applications from scratch in Python

Tyler Richards

Głębokie uczenie przez wzmacnianie. Praca z chatbotami oraz robotyka, optymalizacja dyskretna i automatyzacja sieciowa w praktyce. Wydanie II

Maxim Lapan

Głębokie uczenie. Wprowadzenie

Jacek Tabor, Marek Śmieja, Łukasz Struski, Przemysław Spurek, ...

Głębokie uczenie z TensorFlow. Od regresji liniowej po uczenie przez wzmacnianie

Bharath Ramsundar, Reza Bosagh Zadeh

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

Xuanyi Chew

Google Cloud AI Services Quick Start Guide. Build intelligent applications with Google Cloud AI services

Arvind Ravulavaru

Google Machine Learning and Generative AI for Solutions Architects. ​Build efficient and scalable AI/ML solutions on Google Cloud

Kieran Kavanagh, Priyanka Vergadia

Graph Machine Learning. Take graph data to the next level by applying machine learning techniques and algorithms

Claudio Stamile, Aldo Marzullo, Enrico Deusebio

Hands-On Artificial Intelligence for Beginners. An introduction to AI concepts, algorithms, and their implementation

Patrick D. Smith

Hands-On Artificial Intelligence for Search. Building intelligent applications and perform enterprise searches

Devangini Patel

Hands-On Artificial Intelligence with Java for Beginners. Build intelligent apps using machine learning and deep learning with Deeplearning4j

Nisheeth Joshi

Hands-On Automated Machine Learning. A beginner's guide to building automated machine learning systems using AutoML and Python

Sibanjan Das, Umit Mert Cakmak

Hands-On Computer Vision with Julia. Build complex applications with advanced Julia packages for image processing, neural networks, and Artificial Intelligence

Dmitrijs Cudihins

Hands-On Convolutional Neural Networks with TensorFlow. Solve computer vision problems with modeling in TensorFlow and Python

Iffat Zafar, Giounona Tzanidou, Richard Burton, Nimesh Patel, ...

Hands-On Data Science with Anaconda. Utilize the right mix of tools to create high-performance data science applications

Yuxing Yan, James Yan

Hands-On Data Science with R. Techniques to perform data manipulation and mining to build smart analytical models using R

Vitor Bianchi Lanzetta, Nataraj Dasgupta, Ricardo Anjoleto Farias

Hands-On Deep Learning Algorithms with Python. Master deep learning algorithms with extensive math by implementing them using TensorFlow

Sudharsan Ravichandiran

Hands-On Deep Learning Architectures with Python. Create deep neural networks to solve computational problems using TensorFlow and Keras

Yuxi (Hayden) Liu, Saransh Mehta

Hands-On Deep Learning for Images with TensorFlow. Build intelligent computer vision applications using TensorFlow and Keras

Will Ballard

Hands-On Deep Learning for IoT. Train neural network models to develop intelligent IoT applications

Dr. Mohammad Abdur Razzaque, Md. Rezaul Karim

Hands-On Deep Learning with Go. A practical guide to building and implementing neural network models using Go

Gareth Seneque, Darrell Chua