Uczenie maszynowe

Neural Network Projects with Python. The ultimate guide to using Python to explore the true power of neural networks through six projects

James Loy

Neural Networks with Keras Cookbook. Over 70 recipes leveraging deep learning techniques across image, text, audio, and game bots

V Kishore Ayyadevara

Neural Networks with R. Build smart systems by implementing popular deep learning models in R

Balaji Venkateswaran, Giuseppe Ciaburro

Newtonian Mechanics. Exploring the Principles of Classical Physics from Fundamentals to Advanced Applications

Mercury Learning and Information, Derek Raine

Nowoczesne architektury danych. Przewodnik po hurtowni danych, siatce danych oraz Data Fabric i Data Lakehouse

James Serra

Odsłaniamy SQL Server 2019: Klastry Big Data i uczenie maszynowe

Bob Ward

OpenCV 3 Computer Vision Application Programming Cookbook. Recipes to make your applications see - Third Edition

Robert Laganiere

OpenCV 3.x with Python By Example. Make the most of OpenCV and Python to build applications for object recognition and augmented reality - Second Edition

Gabriel Garrido Calvo, Prateek Joshi

Optimization Using Linear Programming. A Practical Guide to Mastering Linear Programming Techniques

Mercury Learning and Information, A. J. Metei, Veena Jain

Podręcznik architekta rozwiązań. Poznaj reguły oraz strategie projektu architektury i rozpocznij niezwykłą karierę. Wydanie II

Saurabh Shrivastava, Neelanjali Srivastav

Potoki danych. Leksykon kieszonkowy. Przenoszenie i przetwarzanie danych na potrzeby ich analizy

James Densmore

Practical Computer Vision. Extract insightful information from images using TensorFlow, Keras, and OpenCV

Abhinav Dadhich

Practical Convolutional Neural Networks. Implement advanced deep learning models using Python

Mohit Sewak, Md. Rezaul Karim, Pradeep Pujari

Practical Guide to Applied Conformal Prediction in Python. Learn and apply the best uncertainty frameworks to your industry applications

Valery Manokhin, Agus Sudjianto

Practical Machine Learning with R. Define, build, and evaluate machine learning models for real-world applications

Brindha Priyadarshini Jeyaraman, Ludvig Renbo Olsen, Monicah Wambugu

Practical Site Reliability Engineering. Automate the process of designing, developing, and delivering highly reliable apps and services with SRE

Pethuru Raj Chelliah, Shreyash Naithani, Shailender Singh