Programowanie

Practical Machine Learning Cookbook. Supervised and unsupervised machine learning simplified

Atul Tripathi

Practical Machine Learning on Databricks. Seamlessly transition ML models and MLOps on Databricks

Debu Sinha

Practical Microservices with Dapr and .NET. A developer's guide to building cloud-native applications using the Dapr event-driven runtime

Davide Bedin, Mark Russinovich

Practical Model-Driven Enterprise Architecture. Design a mature enterprise architecture repository using Sparx Systems Enterprise Architect and ArchiMate® 3.1

Mudar Bahri, Joe Williams

Practical Node-RED Programming. Learn powerful visual programming techniques and best practices for the web and IoT

Taiji Hagino, Nick O'Leary

Practical OneOps. Implement DevOps with ease

Nilesh Nimkar

Practical Python Programming for IoT. Build advanced IoT projects using a Raspberry Pi 4, MQTT, RESTful APIs, WebSockets, and Python 3

Gary Smart

Practical Security Automation and Testing. Tools and techniques for automated security scanning and testing in DevSecOps

Tony Hsiang-Chih Hsu

Practical Serverless and Microservices with C#. Build resilient and secure microservices with the .NET stack and embrace serverless development in Azure

Gabriel Baptista, Francesco Abbruzzese

Practical System Programming for Rust Developers. Build fast and secure software for Linux/Unix systems with the help of practical examples

Prabhu Eshwarla

Practical Test-Driven Development using C# 7. Unleash the power of TDD by implementing real world examples under .NET environment and JavaScript

John Callaway, Clayton Hunt

Practical Time Series Analysis. Master Time Series Data Processing, Visualization, and Modeling using Python

Avishek Pal, PKS Prakash

Pragmatic Test-Driven Development in C# and .NET. Write loosely coupled, documented, and high-quality code with DDD using familiar tools and libraries

Adam Tibi

Pragmatyczny programista. Od czeladnika do mistrza. Wydanie II

David Thomas, Andrew Hunt

Praktyczna algebra liniowa dla analityków danych. Od podstawowych koncepcji do użytecznych aplikacji w Pythonie

Mike Cohen

Praktyczne uczenie maszynowe w języku R

Fred Nwanganga, Mike Chapple