Scikit-learn Libraries

81 Components & Libraries

Sortby

Scikit-learn Libraries

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

Use any of the following services. Next, run the following commands: Finally, start Jupyter: I recommend Python 3.7. If you follow the installation instructions above, that's the version you will get…

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

The "Python Machine Learning (1st edition)" book code repository and info resource

What you can expect are 400 pages rich in useful material just about everything you need to know to get started with machine learning ... from theory to the actual code that you can directly put into…

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

TPOT will automate the most tedious part of machine learning by intelligently exploring thousands of possible pipelines to find the best one for your data. Once TPOT is finished searching (or you get…

Open Machine Learning Course

mlcourse.ai is still in self-paced mode but we offer you Bonus Assignments with solutions for a contribution of $17/month. The idea is that you pay for ~1-5 months while studying the course materials…

python-machine-learning-book-2nd-edition

The "Python Machine Learning (2nd edition)" book code repository and info resource

published September 20th, 2017 Oh, there are so many things that we improved or added; where should I start!? The one issue on top of my priority list was to fix all the nasty typos that were introdu…

An open source python library for automated feature engineering

Install with pip You can install add-ons individually or all at once by running Below is an example of using Deep Feature Synthesis (DFS) to perform automated feature engineering. In this example, we…

python-machine-learning-book-3rd-edition

The "Python Machine Learning (3rd edition)" book code repository

Code repositories for the 1st and 2nd edition are available at to be published December 12th, 2019

Visual analysis and diagnostic tools to facilitate machine learning model selection.

Yellowbrick is compatible with Python 3.4 or later and also depends on scikit-learn and matplotlib. The simplest way to install Yellowbrick and its dependencies is from PyPI with pip, Python's prefer…

Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.

IPython Notebook(s) and other programming tools such as Torch/Lua/D lang in demonstrating deep learning functionality. Additional PyRo tutorials: IPython Notebook(s) demonstrating scikit-learn functi…

🛠 All-in-one web-based IDE specialized for machine learning and data science.

The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science. It is simple to deploy and gets you started within minutes to productively built ML solutions on you…

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

You can start with this article that I wrote in Heartbeat magazine (on Medium platform): Jupyter notebooks covering a wide range of functions and operations on the topics of NumPy, Pandans, Seaborn, …

A library for debugging/inspecting machine learning classifiers and explaining their predictions

ELI5 is a Python package which helps to debug machine learning classifiers and explain their predictions. It provides support for the following machine learning frameworks and packages: License is MI…

Carefully curated resource links for data science in one place

A trove of carefully curated resources and links (on the topics of software, platforms, language, techniques, etc.) related to data science, all in one place. Homework 3

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

This repository contains all the code, notebooks and examples used in this book. We will also be adding bonus content here from time to time. So keep watching this space! Master the essential skills …

[UNMAINTAINED] Automated machine learning for analytics & production

Automated machine learning for production and analytics auto_ml is designed for production. Here's an example that includes serializing and loading the trained model, then getting predictions on sing…

Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer.

Text analytics can be a bit overwhelming and frustrating at times with the unstructured and noisy nature of textual data and the vast amount of information available. "Text Analytics with Python" is …

Using python and scikit-learn to make stock predictions

While I would not live trade based off of the predictions from this exact code, I do believe that you can use this project as starting point for a profitable trading system – I have actually used cod…

Metric learning algorithms in Python

If you use metric-learn in a scientific publication, we would appreciate citations to the following paper: Bibtex entry:

Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data

Python implementations of the k-modes and k-prototypes clustering algorithms. Relies on numpy for a lot of the heavy lifting. k-modes is used for clustering categorical variables. It defines clusters…

Small scale machine learning projects to understand the core concepts . Give a Star 🌟If it helps you. BONUS: Interview Bank coming up..!

You will get the following, mlwp-test is the env name used in this example The environment is successfully created. Now activate the Conda environment. You will get the following Install the required…

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

With Intel(R) Extension for Scikit-learn, you can: To install Intel(R) Extension for Scikit-learn, run: The software acceleration is achieved through patching. It means, replacing the stock scikit-le…

Automated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost

You should already have pip, Python, and optionally XGBoost, LightGBM, and CatBoost installed on your system (see below). Run the following command to install AlphaPy: Pyfolio is automatically instal…

Machine learning in Python with scikit-learn MOOC

A few different ways are available:

Otto makes machine learning an intuitive, natural language experience. 🏆 Facebook AI Hackathon winner ⭐️ #1 Trending on MadeWithML.com ⭐️ #4 Trending JavaScript Project on GitHub ⭐️ #15 Trending (All Languages) on GitHub

To demo some of Otto's core features, try out the following: And feel free to get creative! Come up with your own machine learning goals and see where Otto takes you. Below is a step-by-step breakdow…

A high-performance topological machine learning toolbox in Python

To run the examples, jupyter is required. Pre-release, experimental builds containing recently added features, and/or bug fixes can be installed by running After developer installation, you can launc…

A machine learning package for streaming data in Python. The other ancestor of River.

We feel that both projects share the same vision. We believe that pooling our resources instead of duplicating work will benefit both sides. We are also confident that this will benefit both communit…

Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries

Automatically save and learn from Experiment results, leading to long-term, persistent optimization that remembers all your tests. HyperparameterHunter provides a wrapper for machine learning algorit…

Related tags