BOOKS - PROGRAMMING - Practical Data Science with R, 2nd Edition
Practical Data Science with R, 2nd Edition - Nina Zumel, John Mount 2020 PDF Manning Publications BOOKS PROGRAMMING
ECO~19 kg CO²

2 TON

Views
23413

Telegram
 
Practical Data Science with R, 2nd Edition
Author: Nina Zumel, John Mount
Year: 2020
Pages: 568
Format: PDF
File size: 24.2 MB
Language: ENG



Pay with Telegram STARS
''

You may also be interested in:

Introducing Data Science Big data, machine learning, and more, using Python tools
Becoming a Data Head: How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning
Analytics in a Big Data World The Essential Guide to Data Science and its Applications
Becoming a Data Head How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning
Learning Data Science: Data Wrangling, Exploration, Visualization, and Modeling with Python
Introduction to Data Science Data Wrangling and Visualization with R, 2nd Edition
Python Data Science Handbook: Essential Tools for Working with Data
Data Mining and Exploration From Traditional Statistics to Modern Data Science
R for Data Science Import, Tidy, Transform, Visualize, and Model Data
Agile Data Science Building Data Analytics Applications with Hadoop
Effective Data Science Infrastructure How to Make Data Scientists Productive
Python Data Science Handbook Essential Tools for Working with Data
The Data Preparation Journey: Finding Your Way with R (Chapman and Hall CRC Data Science Series)
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)
Training Data for Machine Learning Human Supervision from Annotation to Data Science (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
Training Data for Machine Learning Human Supervision from Annotation to Data Science (Final)
Humanizing Big Data: Marketing at the Meeting of Data, Social Science and Consumer Insight
Univariate, Bivariate, and Multivariate Statistics Using R Quantitative Tools for Data Analysis and Data Science
Learning Data Science Data Wrangling, Exploration, Visualization, and Modeling with Python (Final)
Agile Data Science 2.0 Building Full-Stack Data Analytics Applications with Spark
Data Science From Scratch From Data Visualization To Manipulation. It Is The Easy Way! All You Need For Business Using The Basic Principles Of Python And Beyond
Data Science in Chemistry: Artificial Intelligence, Big Data, Chemometrics and Quantum Computing with Jupyter
Computer Science in Sport Modeling, Simulation, Data Analysis and Visualization of Sports-Related Data
Programming Skills for Data Science Start Writing Code to Wrangle, Analyze, and Visualize Data with R
Computer Science in Sport Modeling, Simulation, Data Analysis and Visualization of Sports-Related Data
Computer Science in Sport: Modeling, Simulation, Data Analysis and Visualization of Sports-Related Data
Data Smart: Using Data Science, 2nd Ed. Jordan Goldmeier
Data Science and Big Data Analytics in Smart Environments
Advances in Data Science Symbolic, Complex, and Network Data
Data Science and Analytics with Python (Chapman and Hall CRC Data Mining and Knowledge Discovery Series)
Beginning Mathematica and Wolfram for Data Science: Applications in Data Analysis, Machine Learning, and Neural Networks
Python Data Science The Ultimate Crash Course, Tips, and Tricks to Learn Data Analytics, Machine Learning, and Their Application
Data Science in Chemistry Artificial Intelligence, Big Data, Chemometrics and Quantum Computing with Jupyter (De Gruyter Textbook)
Advanced Data Science and Analytics with Python (Chapman and Hall CRC Data Mining and Knowledge Discovery Series)
Essential Math for Data Science Take Control of Your Data with Fundamental Linear Algebra, Probability, and Statistics (Third Early Release)
Data Science Fundamentals with R, Python, and Open Data
Data Science with Python From Data Wrangling to Visualization