Big data

Practical Data Wrangling. Expert techniques for transforming your raw data into a valuable source for analytics

Allan Visochek

Practical Deep Learning at Scale with MLflow. Bridge the gap between offline experimentation and online production

Yong Liu, Dr. Matei Zaharia

Practical GIS. Learn novice to advanced topics such as QGIS, Spatial data analysis, and more

Gábor Farkas

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 Cookbook. Supervised and unsupervised machine learning simplified

Atul Tripathi

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

Brindha Priyadarshini Jeyaraman, Ludvig Renbo Olsen, Monicah...

Practical Predictive Analytics. Analyse current and historical data to predict future trends using R, Spark, and more

Ralph Winters

Practical Real-time Data Processing and Analytics. Distributed Computing and Event Processing using Apache Spark, Flink, Storm, and Kafka

Shilpi Saxena, Saurabh Gupta

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

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

Practical Threat Intelligence and Data-Driven Threat Hunting. A hands-on guide to threat hunting with the ATT&CK™ Framework and open source tools

Valentina Costa-Gazcón

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

Avishek Pal, PKS Prakash

Praktyczne uczenie maszynowe w języku R

Fred Nwanganga, Mike Chapple

Praktyczne uczenie nienadzorowane przy użyciu języka Python

Ankur A. Patel

Principles of Data Science. A beginner's guide to essential math and coding skills for data fluency and machine learning - Third Edition

Sinan Ozdemir

Principles of Data Science. Mathematical techniques and theory to succeed in data-driven industries

Sinan Ozdemir

Principles of Data Science. Understand, analyze, and predict data using Machine Learning concepts and tools - Second Edition

Sinan Ozdemir, Sunil Kakade, Marco Tibaldeschi

Principles of Strategic Data Science. Creating value from data, big and small

Peter Prevos

Privacy-Preserving Machine Learning. A use-case-driven approach to building and protecting ML pipelines from privacy and security threats

Srinivasa Rao Aravilli, Sam Hamilton

Programming PowerPoint With VBA Straight to the Point. Harness VBA to Customize, Automate, and Revolutionize PowerPoint Presentations

MrExcel's Holy Macro! Books, Eduardo N Sanchez

Projektowanie aplikacji LLM. Holistyczne podejście do dużych modeli językowych

Suhas Pai

Projektowanie głosowych interfejsów użytkownika. Zasady doświadczeń konwersacyjnych

Cathy Pearl

Puppet 3 Cookbook. An essential book if you have responsibility for servers. Real-world examples and code will give you Puppet expertise, allowing more control over servers, cloud computing, and desktops. A time-saving, career-enhancing tutorial - Second Edition

John Arundel

PySpark Cookbook. Over 60 recipes for implementing big data processing and analytics using Apache Spark and Python

Denny Lee, Tomasz Drabas

Python 3 and Data Analytics Pocket Primer. A Quick Guide to NumPy, Pandas, and Data Visualization

Mercury Learning and Information, Oswald Campesato