BOOKS - OS AND DB - Game Data Science
Game Data Science - Magy Seif El-Nasr, Truong-Huy D. Nguyen, Alessandro Canossa, Anders Drachen 2021 PDF Oxford University Press BOOKS OS AND DB
ECO~18 kg CO²

1 TON

Views
89630

Telegram
 
Game Data Science
Author: Magy Seif El-Nasr, Truong-Huy D. Nguyen, Alessandro Canossa, Anders Drachen
Year: 2021
Pages: 414
Format: PDF
File size: 10 MB
Language: ENG



Pay with Telegram STARS
''

You may also be interested in:

Python for Data Science Comprehensive Guide of Tips and Tricks using Python Data Science
Data Science From Scratch Comprehensive Beginners Guide To Learn Data Science From Scratch
Python for Data Science Advanced and Effective Strategies of Using Python Data Science Theories
Practical Data Science with Jupyter Explore Data Cleaning, Pre-processing, Data Wrangling, Feature Engineering and Machine Learning using Python and Jupyter
Data Science Projects with Python: A case study approach to successful data science projects using Python, pandas, and scikit-learn
The Craft and Science of Game Design A Video Game Designer|s Manual
Big data A Guide to Big Data Trends, Artificial Intelligence, Machine Learning, Predictive Analytics, Internet of Things, Data Science, Data Analytics, Business Intelligence, and Data Mining
Big Data Demystified: How to use big data, data science and AI to make better business decisions and gain competitive advantage
Python Data Science An Essential Crash Course Made Accessible to Start Working With Essential Tools, Techniques and Concepts that Help you Learn Python Data Science (python for beginners Book 2)
Business Intelligence An Essential Beginner’s Guide to BI, Big Data, Artificial Intelligence, Cybersecurity, Machine Learning, Data Science, Data Analytics, Social Media and Internet Marketing
Python For Data Science The Ultimate Beginners’ Guide to Learning Python Data Science Step by Step
Becoming a Data Head: How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning
Becoming a Data Head How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning
Data Smart Using Data Science to Transform Information into Insight, 2nd Edition
Learning Data Science: Data Wrangling, Exploration, Visualization, and Modeling with Python
Introducing Data Science Big data, machine learning, and more, using Python tools
Analytics in a Big Data World The Essential Guide to Data Science and its Applications
Data Smart Using Data Science to Transform Information into Insight, 2nd Edition
Effective Data Science Infrastructure How to Make Data Scientists Productive
Python Data Science Handbook Essential Tools for Working with Data
R for Data Science Import, Tidy, Transform, Visualize, and Model Data
Agile Data Science Building Data Analytics Applications with Hadoop
Data Mining and Exploration From Traditional Statistics to Modern Data Science
Python Data Science Handbook: Essential Tools for Working with Data
Introduction to Data Science Data Wrangling and Visualization with R, 2nd Edition
Learning Data Science Data Wrangling, Exploration, Visualization, and Modeling with Python (Final)
Training Data for Machine Learning Human Supervision from Annotation to Data Science (Final)
Univariate, Bivariate, and Multivariate Statistics Using R Quantitative Tools for Data Analysis and Data Science
Training Data for Machine Learning Human Supervision from Annotation to Data Science (Final)
Practical Data Science with SAP Machine Learning Techniques for Enterprise Data, First Edition
Humanizing Big Data: Marketing at the Meeting of Data, Social Science and Consumer Insight
Effective Data Science Infrastructure How to make data scientists productive (MEAP Version 7)
Learning Data Science Data Wrangling, Exploration, Visualization, and Modeling with Python (Final)
The Real Work of Data Science Turning data into information, better decisions, and stronger organizations
Data Science Essentials with R Learn with focus on data manipulation, visualization, and machine learning
The Data Preparation Journey: Finding Your Way with R (Chapman and Hall CRC Data Science Series)
Agile Data Science 2.0 Building Full-Stack Data Analytics Applications with Spark
R Graphics Essentials for Great Data Visualization +200 Practical Examples You Want to Know for Data Science
Computer Science in Sport Modeling, Simulation, Data Analysis and Visualization of Sports-Related Data
Practical Data Science with SAP Machine Learning Techniques for Enterprise Data, Early Release