BOOKS - PROGRAMMING - An Introduction to Statistical Learning with Applications in R,...
An Introduction to Statistical Learning with Applications in R, 2nd Edition - Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani 2021 PDF Sptinger BOOKS PROGRAMMING
ECO~23 kg CO²

2 TON

Views
64945

Telegram
 
An Introduction to Statistical Learning with Applications in R, 2nd Edition
Author: Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
Year: 2021
Pages: 616
Format: PDF
File size: 13,7 MB
Language: ENG



Pay with Telegram STARS
''

You may also be interested in:

Differing visions of a Learning Society Vol 2: Research findings Volume 2 (ESRC Learning Society series)
Machine Learning The Ultimate Guide to Understand AI Big Data Analytics and the Machine Learning’s Building Block Application in Modern Life
Deep Learning fur die Biowissenschaften Einsatz von Deep Learning in Genomik, Biophysik, Mikroskopie und medizinischer Analyse
Deep Learning for Finance Creating Machine & Deep Learning Models for Trading in Python
Machine Learning A Guide to PyTorch, TensorFlow, and Scikit-Learn Mastering Machine Learning With Python
Deep Learning for Data Architects Unleash the power of Python|s deep learning algorithms
Machine Learning with Core ML 2 and Swift A beginner-friendly guide to integrating machine learning into your apps
Human-in-the-Loop Machine Learning Active learning, annotation and human-computer interaction (MEAP)
Anatomy of Deep Learning Principles: Writing a deep learning library from scratch (Japanese Edition)
Learning Google Cloud Vertex AI Build, deploy, and manage machine learning models with Vertex AI
Machine Learning A Guide to PyTorch, TensorFlow, and Scikit-Learn Mastering Machine Learning With Python
Active Machine Learning with Python: Refine and elevate data quality over quantity with active learning
Machine Learning for Beginners Build and deploy Machine Learning systems using Python, 2nd Edition
Robust Machine Learning: Distributed Methods for Safe AI (Machine Learning: Foundations, Methodologies, and Applications)
Machine Learning: A Guide to PyTorch, TensorFlow, and Scikit-Learn: Mastering Machine Learning With Python
Deep Learning for the Life Sciences Applying Deep Learning to Genomics, Microscopy, Drug Discovery, and More
Deep Learning for Finance Creating Machine & Deep Learning Models for Trading in Python
Learning Google Cloud Vertex AI Build, deploy, and manage machine learning models with Vertex AI
Deep Learning for Data Architects Unleash the power of Python|s deep learning algorithms
Learning to Love (The Learning Trilogy #3)
Learning Race, Learning Place
From Machine Learning To Deep Learning
Learning to Move Forward (Learning, #3.5)
Programming Machine Learning Machine Learning Basics Concepts + Artificial Intelligence + Python Programming + Python Machine Learning
Programming Machine Learning Machine Learning Basics Concepts + Artificial Intelligence + Python Programming + Python Machine Learning
Probability Theory and Statistical Applications: A Profound Treatise for Self-Study (De Gruyter Textbook)
Operation Barbarossa The Complete Organisational and Statistical Analysis, and Military Simulation Volume I
Probably Overthinking It: How to Use Data to Answer Questions, Avoid Statistical Traps, and Make Better Decisions
Statistical Inference via Convex Optimization (Princeton Series in Applied Mathematics Book 69)
Warfare and Armed Conflicts A Statistical Encyclopedia of Casualty and Other Figures, 1492-2015
Computational Statistical Methodologies and Modeling for Artificial Intelligence (Edge AI in Future Computing)
A Method for Studying Model Hamiltonians: A Minimax Principle for Problems in Statistical Physics
Learn AI with Python: Explore Machine Learning and Deep Learning techniques for Building Smart AI Systems Using Scikit-Learn, NLTK, NeuroLab, and Keras
Learn Autonomous Programming with Python Utilize Python|s capabilities in Artificial Intelligence, Machine Learning, Deep Learning and robotic process automation
Deep Learning and AI Superhero Mastering TensorFlow, Keras, and PyTorch Advanced Machine Learning and AI, Neural Networks, and Real-World Projects (Mastering the AI Revolution)
Learn Autonomous Programming with Python Utilize Python|s capabilities in Artificial Intelligence, Machine Learning, Deep Learning and robotic process automation
Machine Learning for Beginners A Practical Guide to Understanding and Applying Machine Learning Concepts
Machine Learning and Deep Learning in Computational Toxicology (Computational Methods in Engineering and the Sciences)
Machine Learning for Finance Master Financial Strategies with Python-Powered Machine Learning
Machine Learning, Animated (Chapman and Hall CRC Machine Learning and Pattern Recognition)