5 Statsmodels Functions That Give You the "Why" Behind the "What"

Statsmodels answers the questions sklearn was never built to answer: is this coefficient real or noise, does this added complexity earn its keep, can I trust these p-values in the first place, and which specific data points are quietly running the whole show.

Note: Run a regression in scikit-learn, and you get exactly two things back: a set of coefficients and a .predict() method. Ask it for a p-value on any of those coefficients, and there’s no built-in way to get one. This isn’t a missing feature scikit-learn’s maintainers overlooked; it’s a deliberate design choice they’ve stated directly: scikit-learn is built for prediction, not statistical inference…

Olivier Grisel - Predictive survival analysis with scikit-learn, scikit-survival and lifelines

Tune In: Decision Threshold Optimization with scikit-learn’s TunedThreshold

Use cases and code to explore the new class that helps tune decision thresholds in scikit-learn.

skfolio/skfolio

Python library for portfolio optimization built on top of scikit-learn - skfolio/skfolio

Install scikit-learn in Jupyter Lab

Shared via ChatGPT

iryna-kondr/scikit-llm: Seamlessly integrate LLMs into scikit-learn.

Seamlessly integrate LLMs into scikit-learn.

Sklearn Pipelines for the Modern ML Engineer: 9 Techniques You Can’t Ignore

Master Sklearn pipelines for effortless and efficient machine learning. Discover the art of building, optimizing, and scaling models with ease. Level up your data preprocessing skills and supercharge your ML workflow today

Make your sklearn models up to 100 times faster

How to considerable reduce training time changing only 1 line of code

skops: a new library to improve scikit-learn in production

There are various challenges in MLOps and model sharing, including, security and reproducibility. To tackle these for scikit-learn models, we've developed a new open-source library: skops. In this article, I will walk you through how it works and how to use it with an end-to-end…

7 Scikit-Learn Best Practices For Data Scientists

Tips for taking full advantage of this machine learning package

2 Ways to Build Your Own Custom Scikit Learn Transformers

How you can (and why you should) create custom transformers

Scikit-learn 1.1 Comes with an Improved OneHotEncoder

A simple yet highly practical feature

Converting Text Documents to Token Counts with CountVectorizer

The post explains the significance of CountVectorizer and demonstrates its implementation with Python code.

Build Complex Time Series Regression Pipelines with sktime

How to forecast with scikit-learn and XGBoost models with sktime

scikit-learn-contrib/imbalanced-learn: A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning - scikit-learn-contrib/imbalanced-learn

Reproducible ML: Maybe you shouldn’t be using Sklearn’s train_test_split

Reproducibility is critical for robust data science — after all, it is a science.

One Line of Code to Accelerate Your Sklearn Algorithms on Big Data

The introduction of the intel sklearn extension. Make your Random Forest even faster than XGBoost.

scikit-learn/README.md at master · bjpcjp/scikit-learn

Updates in progress. Jupyter workbooks will be added as time allows. - bjpcjp/scikit-learn

python-data-science-handbook/scikit/SciKit-Feature-Engineering.ipynb at master · bjpcjp/python-data-science-handbook

Sourced from O'Reilly ebook of the same name.

scikit-and-tensorflow-workbooks/ch03-classification.ipynb at master · bjpcjp/scikit-and-tensorflow-workbooks

based on "Hands-On Machine Learning with Scikit-Learn & TensorFlow" (O'Reilly, Aurelien Geron) - bjpcjp/scikit-and-tensorflow-workbooks

scikit-learn/64_imputation.ipynb at master · bjpcjp/scikit-learn

Updates in progress. Jupyter workbooks will be added as time allows. - bjpcjp/scikit-learn

python-data-science-handbook/scikit/SciKit-Kernel-Density-Estimation.ipynb at master · bjpcjp/python-data-science-handbook

Sourced from O'Reilly ebook of the same name.

scikit-learn/63_preprocessing.ipynb at master · bjpcjp/scikit-learn

Updates in progress. Jupyter workbooks will be added as time allows. - bjpcjp/scikit-learn

scikit-learn/62a_text_feature_extraction.ipynb at master · bjpcjp/scikit-learn

Updates in progress. Jupyter workbooks will be added as time allows. - bjpcjp/scikit-learn

A Practical Introduction to 9 Regression Algorithms

Hands-on tutorial to effectively use different Regression Algorithms

What Is The Difference Between predict() and predict_proba() in scikit-lear

How to use predict and predict_proba methods over a dataset in order to perform predictions

Scikit-Learn Version 1.0

For a short description of the main highlights of the release, please refer to Release Highlights for scikit-learn 1.0. Legend for changelogs something big that you couldn’t do before., something t...

scikit-learn-intelex · PyPI

Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application.

11 Dimensionality reduction techniques you should know in 2021

Reduce the size of your dataset while keeping as much of the variation as possible

Deep In Singular Value Decomposition

There are often times when working in Data Science where we might come across a feature that is very difficult to interpret by a computer. This is often because the dimensions of the data are much…

A Summary of Active Learning Frameworks

If you are dealing with a classification task, I recommend the modAL. As for the sequence labeling task, the AlpacaTag is the only choice for you. Active learning could decrease the number of labels…

How to create custom scikit-learn classification and regression models

Scikit learn is *the* go to package for standard machine learning models in Python. It not only provides most of the core algorithms that…

11 Times Faster Hyperparameter Tuning with HalvingGridSearch

Successive halving completely crushes GridSearch and RandomSearch

Data Science Plumbing: Peeking Into Scikit-Learn Pipelines

Have you ever wondered how to extract information from a scikit-learn pipeline?

The Ultimate Scikit-Learn Machine Learning Cheatsheet - KDnuggets

With the power and popularity of the scikit-learn for machine learning in Python, this library is a foundation to any practitioner's toolset. Preview its core methods with this review of predictive modelling, clustering, dimensionality reduction, feature importance, and data…

New Features of Scikit-Learn. An Overview of the Most Important… | by Ankit

An Overview of the Most Important Features in Version 0.24

Make kNN 300 times faster than Scikit-learn’s in 20 lines!

Using Facebook faiss library for REALLY fast kNN

How to Extend Scikit-learn and Bring Sanity to Your Machine Learning Workflow - KDnuggets

In this post, learn how to extend Scikit-learn code to make your experiments easier to maintain and reproduce.

SciKit-Learn Laboratory (SKLL) — SciKit-Learn Laboratory 1.5 documentation

reiinakano/scikit-plot: An intuitive library to add plotting functionality

An intuitive library to add plotting functionality to scikit-learn objects. - reiinakano/scikit-plot

Integrating LLMs with Scikit-Learn Using Scikit-LLM

Combining LLM reasoning for text-based models in Scikit-Learn.