Machine-learning-algorithms Libraries

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Machine-learning-algorithms Libraries

Implementation of different ML Algorithms from scratch, written in Python 3.x

Implementation of different machine learning algorithms written in Python. NOTE: scikit-learn module is used only for accessing the datasets and scalers. NOTE: All scripts have additional command arg…

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

To install the current release: Participating discussions via the following IM groups is also welcomed. Over the past few years, NNI has received thousands of feedbacks on GitHub issues, and pull req…

StellarGraph - Machine Learning on Graphs

Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes. For example, a graph can…

This is a Python 3.0 project for analyzing stock prices and methods of stock trading. It uses native Python tools and Google TensorFlow machine learning.

This is a Python 3.0 project for analyzing stock prices and methods of stock trading. It uses native Python tools and Google TensorFlow machine learning. It has two main class modules PriceTradeAnaly…

Plain python implementations of basic machine learning algorithms

If you have a favorite algorithm that should be included or spot a mistake in one of the notebooks, please let me know by creating a new issue. See the LICENSE file for license rights and limitations…

machine learning

The overall objective of this toolkit is to provide and offer a free collection of data analysis and machine learning that is specifically suited for doing data science. Its purpose is to get you started in a matter of minutes. You can run this collections either in Jupyter notebook or python alone.

The overall objective of this toolkit is to provide and offer a free collection of data analysis and machine learning that is specifically suited for doing data science. Its purpose is to get you sta…

Machine Learning notebooks for refreshing concepts.

Helpful jupyter noteboks that I compiled while learning Machine Learning and Deep Learning from various sources on the Internet. Linear & Multiple Regression Logistic Regression Regularization

Deep & Classical Reinforcement Learning + Machine Learning Examples in Python

We provide here a suite of Python examples that walk you through concepts in: Classical & Deep Reinforcement Learning Basic & Advanced Machine Learning Anson Wong

Data-Science-and-Machine-Learning-from-Scratch

Implements common data science methods and machine learning algorithms from scratch in python. Intuition and theory behind the algorithms is also discussed.

I write the notebooks to contain: Intuition Mathematics and Statistics behind the tool/algorithm Code implementation from scratch (using numpy) Application to real (publicly available) data If you sp…

Solutions to the 'Applied Machine Learning In Python' Coursera course exercises

The machine learning toolkit for time series analysis in Python

There are different alternatives to install tslearn:

A repository for the source code, notebooks, data, files, and other assets used in the data science and machine learning articles on LearnDataSci

A repository for the code, files, and other assets used in LearnDataSci articles. Links to posts on LearnDataSci and their repos (sorted by recency):

Collection of lectures and lab lectures on machine learning and deep learning. Lab practices in Python and TensorFlow.

Notes, examples, and Python demos for the 2nd edition of the textbook "Machine Learning Refined" (published by Cambridge University Press).

We believe mastery of a certain machine learning concept/topic is achieved only when the answer to each of the following three questions is affirmative. Example ”roadmaps” shown below provide suggest…

An extensive machine learning library, made from scratch (Python).

This is a machine learning library, made from scratch. It uses: It contains the following functionality: Examples are shown in two dimensions for visualisation purposes, however, all methods can hand…

Code for Agile Data Science 2.0, O'Reilly 2017, Second Edition

It was last updated to a fully running version in late October, 2021. You should refer to the Jupyter Notebooks in this repository rather than the book's source code, which is badly outdated and will…

Information about my experiences in cybersecurity :skull:

Information about my cybersecurity experiences ... This repository is divided by the next sections: Bibliography

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…

NoteBooks-Statistics-and-MachineLearning

Jupyter Notebooks from the old UnsupervisedLearning.com (RIP) machine learning and statistics blog

Notebooks as published on unsupervised-learning.com (RIP).

Python toolkit for pluggable algorithms and data structures for multimedia-based machine learning.

As of Jan 2021, SMQTK v0.14.0 has been deprecated. The various interfaces and implementations have been broken out into the following distinct packages which will continue to be supported instead. So…