What to Read After An Introduction To Statistical Learning With Applications In R
Readers who loved An Introduction To Statistical Learning With Applications In R by Gareth James keep reaching for these 24 books. This list is built from where An Introduction To Statistical Learning With Applications In R is read alongside other books across reader co-reads and book lists. The more independent sources agree on a title, the higher it ranks.
Books to read after An Introduction To Statistical Learning With Applications In R
The Elements of Statistical Learning
The art of R programming
Python For Data Analysis
Doing Data Science
Pattern Recognition and Machine Learning (Information Science and Statistics)
Data Analysis with Open Source Tools
Probabilistic Graphical Models
Mining of Massive Datasets
Mathematical proofs
Python machine learning
Learning Spark: Lightning-Fast Big Data Analysis
Data Science for Business
Programming Collective Intelligence
How to Measure Anything
Think STATS
R cookbook
R in a nutshell
Machine Learning (Mcgraw-Hill International Edit)
Think Python
Introduction to linear algebra
Elements of programming interviews
Linear algebra and its applications
The Master Algorithm
Functional Programming in Scala
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