An Introduction to Statistical Learning with applications in PYTHON!
As the scale and scope of data collection continue to increase across virtually all fields, statistical learning has become a critical toolkit for anyone who wishes to understand data. An Introduction to Statistical Learning provides a broad and less technical treatment of key topics in statistical learning.
The Python edition (ISLP) was published in 2023.
The chapters cover the following topics:
- What is statistical learning?
- Regression
- Classification
- Resampling methods
- Linear model selection and regularization
- Moving beyond linearity
- Tree-based methods
- Support vector machines
- Deep learning
- Survival analysis
- Unsupervised learning
- Multiple testing
Link: https://www.statlearning.com
Navigational hashtags: #armknowledgesharing #armbooks
General hashtags: #ISLR #ISLP #regression #classification #resampling #linearmodels #regularization #trees #svm #deeplearning #unsupervisedlearning #abtesting
@data_science_weekly
As the scale and scope of data collection continue to increase across virtually all fields, statistical learning has become a critical toolkit for anyone who wishes to understand data. An Introduction to Statistical Learning provides a broad and less technical treatment of key topics in statistical learning.
The Python edition (ISLP) was published in 2023.
The chapters cover the following topics:
- What is statistical learning?
- Regression
- Classification
- Resampling methods
- Linear model selection and regularization
- Moving beyond linearity
- Tree-based methods
- Support vector machines
- Deep learning
- Survival analysis
- Unsupervised learning
- Multiple testing
Link: https://www.statlearning.com
Navigational hashtags: #armknowledgesharing #armbooks
General hashtags: #ISLR #ISLP #regression #classification #resampling #linearmodels #regularization #trees #svm #deeplearning #unsupervisedlearning #abtesting
@data_science_weekly