210 Open source projects that are alternatives of or similar to Machine-Learning-Andrew-Ng

该存储库包含由deeplearning.ai提供的相关课程的个人的笔记和实现代码。

Python implementation of Andrew Ng's ML course projects

Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.

Python code for common Machine Learning Algorithms

A Python package to build predictive linear and logistic regression models focused on performance and interpretation

Variational Bayes linear and logistic regression

Tracking, notes and programming snippets while learning predictive analytics

Machine Learning models from scratch with a better visualisation

machine learning algorithm

MATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20

Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.

By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.

In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.

I will update this repository to learn Machine learning with python with statistics content and materials

100 Days of ML Coding

Matlab library for gradient descent algorithms: Version 1.0.1

Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means

A New, Interactive Approach to Learning Python

Machine Learning Course @ Santa Clara University

Data Science & Machine Learning projects and tutorials in python from beginner to advanced level.

An introductory statistics course for social scientists, using Stata

A set of machine learning experiments in Clojure

Deep Learning From Scratch

Collection of various implementations and Codes in Machine Learning, Deep Learning and Computer Vision ✨💥

Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.

A blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.

🧠👨‍💻Deep Learning Specialization • Lecture Notes • Lab Assignments

Plain python implementations of basic machine learning algorithms

Unofficial Stanford's CS229 Machine Learning Problem Solutions (summer edition 2019, 2020).

📈 Regression and Classification with UC Davis student quiz data and exam data

Simple machine learning library / 簡單易用的機器學習套件

General Assembly's 2015 Data Science course in Washington, DC

Artificial intelligence/machine learning course at UCF in Spring 2020 (Fall 2019 and Spring 2019)

This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.

中文文本分类实践，基于搜狗新闻语料库，采用传统机器学习方法以及预训练模型等方法

Basis Function Expansions for Julia

This package can be used for dominance analysis or Shapley Value Regression for finding relative importance of predictors on given dataset. This library can be used for key driver analysis or marginal resource allocation models.

Implementation of models in our EMNLP 2019 paper: A Logic-Driven Framework for Consistency of Neural Models

Final project of IBM's course https://www.coursera.org/learn/machine-learning-with-python on coursera

Heart Disease Analysis repository

This repository will contain all the stuffs required for beginners in ML and DL do follow and star this repo for regular updates

Testing doing basic regression with web assembly

Interactive Visual Machine Learning Demos.

Machine Learning Procedures and Functions for Neo4j

This is a repository of my coursera Machine Learning by Standford, Andrew NG course's assignments

📈 Useful notes and personal collections on statistics.

Solve many kinds of least-squares and matrix-recovery problems

All notes and materials for the CS229: Machine Learning course by Stanford University

Basic Machine Learning implementation with python

AI Learning Hub for Machine Learning, Deep Learning, Computer Vision and Statistics

Loan Application Data Analysis

Deep Learning Specialization Course by Coursera. Neural Networks, Deep Learning, Hyper Tuning, Regularization, Optimization, Data Processing, Convolutional NN, Sequence Models are including this Course.

Tensorflow implementation of the Manifold Mixup machine learning research paper

Predicting the winner of 2019 cricket world cup using random forest algorithm

Pipeline for fast building text classification TF-IDF + LogReg baselines.

A document covering machine learning basics. 🤖📊

📈 Click-Through Rate Prediction using Logistic Regression and Tree Algorithms

A MATLAB toolbox for classifier: Version 1.0.7

โค้ดประกอบเนื้อหา Python Machine Learning เบื้องต้น [2020]

[ICLR'21] PyTorch code for our paper "Neural Pruning via Growing Regularization"