Debugging Machine Learning Models with Python. Develop high-performance, low-bias, and explainable machine learning and deep learning models

Ali Madani, Stephen MacKinnon

Debugging Teams. Przez współpracę do lepszej produktywności

Brian W. Fitzpatrick, Ben Collins-Sussman

Debunking C++ Myths. Embark on an insightful journey to uncover the truths behind popular C++ myths and misconceptions

Alexandru Bolboacă, Ferenc-Lajos Deák

Decentralized Identity Explained. Embrace decentralization for a more secure and empowering digital experience

Rohan Pinto

Deciphering Object-Oriented Programming with C++. A practical, in-depth guide to implementing object-oriented design principles to create robust code

Dorothy R. Kirk

Decoding Large Language Models. An exhaustive guide to understanding, implementing, and optimizing LLMs for NLP applications

Irena Cronin

Decyzyjni. Jak zwykli ludzie kreują niezwykłe produkty

Marty Cagan, Chris Jones

Deep Inside osCommerce: The Cookbook. Ready-to-use recipes to customize and extend your e-commerce website

Monika Mathe, Monika Math?É?íÂ!(C)

Deep Learning and XAI Techniques for Anomaly Detection. Integrate the theory and practice of deep anomaly explainability

Cher Simon, Jeff Barr

Deep Learning By Example. A hands-on guide to implementing advanced machine learning algorithms and neural networks

Ahmed Menshawy

Deep learning dla programistów. Budowanie aplikacji AI za pomocą fastai i PyTorch

Jeremy Howard, Sylvain Gugger

Deep Learning Essentials. Your hands-on guide to the fundamentals of deep learning and neural network modeling

Wei Di, Jianing Wei, Anurag Bhardwaj

Deep Learning for Beginners. A beginner's guide to getting up and running with deep learning from scratch using Python

Dr. Pablo Rivas, Laura Montoya

Deep Learning for Computer Vision. Expert techniques to train advanced neural networks using TensorFlow and Keras

Rajalingappaa Shanmugamani

Deep Learning for Genomics. Data-driven approaches for genomics applications in life sciences and biotechnology

Upendra Kumar Devisetty

Deep Learning for Natural Language Processing. Solve your natural language processing problems with smart deep neural networks

Karthiek Reddy Bokka, Shubhangi Hora, Tanuj Jain, Monicah Wambugu

Deep Learning for Time Series Cookbook. Use PyTorch and Python recipes for forecasting, classification, and anomaly detection

Vitor Cerqueira, Luís Roque

Deep Learning from the Basics. Python and Deep Learning: Theory and Implementation

Koki Saitoh

Deep learning i modelowanie generatywne. Jak nauczyć komputer malowania, pisania, komponowania i grania

David Foster

Deep Learning. Praca z językiem Python i biblioteką Keras

Francois Chollet

Deep Learning. Praca z językiem R i biblioteką Keras

Francois Chollet, J. J. Allaire

Deep Learning: Practical Neural Networks with Java. Build and run intelligent applications by leveraging key Java machine learning libraries

Fabio M. Soares, Boštjan Kaluža, Alan M. F. Souza, Yusuke Sugomori

Deep Learning. Praktyczne wprowadzenie

Josh Patterson, Adam Gibson

Deep Learning Quick Reference. Useful hacks for training and optimizing deep neural networks with TensorFlow and Keras

Mike Bernico