100 Days of ML Coding

Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG

Collection of notebooks about quantitative finance, with interactive python code.

Code for Tensorflow Machine Learning Cookbook

Python code for common Machine Learning Algorithms

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

Plain python implementations of basic machine learning algorithms

Bare bone examples of machine learning in TensorFlow

For extensive instructor led learning

🙄 Difficult algorithm, Simple code.

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

🤖 MatLab/Octave examples of popular machine learning algorithms with code examples and mathematics being explained

gesture recognition toolkit

Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall

Master the Toolkit of AI and Machine Learning. Mathematics for Machine Learning and Data Science is a beginner-friendly Specialization where you’ll learn the fundamental mathematics toolkit of machine learning: calculus, linear algebra, statistics, and probability.

Linear Prediction Model with Automated Feature Engineering and Selection Capabilities

Compendium of free ML reading resources

Fast Best-Subset Selection Library

Multivariable regression library in Go

The official code repository supporting the book, Grokking Artificial Intelligence Algorithms

Regression, Scrapers, and Visualization

The full collection of Jupyter Notebook labs from Andrew Ng's Machine Learning Specialization.

A Julia package for multivariate statistics and data analysis (e.g. dimension reduction)

Machine Learning Lectures at the European Space Agency (ESA) in 2018

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

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。

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

My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge. Now supported by bright developers adding their learnings :+1:

Implementation of basic ML algorithms from scratch in python...

this repository features assignments and projects from the iNeuron full stack data science course, providing valuable resources for learners to enhance their skills and apply their knowledge.