Bare bone examples of machine learning in TensorFlow
吴恩达机器学习coursera课程，学习代码(2017年秋) The Stanford Coursera course on MachineLearning with Andrew Ng
Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
Deep Math Machine Learning.ai
A blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.
100 Days Of Ml Code
A day to day plan for this challenge. Covers both theoritical and practical aspects
Aulas da Escola de Inteligência Artificial de São Paulo
Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.
Machine Learning Models
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
Starter code of Prof. Andrew Ng's machine learning MOOC in R statistical language
My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge.
A simple machine learning framework written in Swift 🤖
General Assembly's 2015 Data Science course in Washington, DC
Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.
Stock Market Prediction Web App Using Machine Learning And Sentiment Analysis
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
Generates and evaluates D, I, A, Alias, E, T, G, and custom optimal designs. Supports generation and evaluation of mixture and split/split-split/N-split plot designs. Includes parametric and Monte Carlo power evaluation functions. Provides a framework to evaluate power using functions provided in other packages or written by the user.
Ds and ml projects
Data Science & Machine Learning projects and tutorials in python from beginner to advanced level.
I will update this repository to learn Machine learning with python with statistics content and materials
Collection of various implementations and Codes in Machine Learning, Deep Learning and Computer Vision ✨💥
A set of machine learning experiments in Clojure
gesture recognition toolkit
Machine Learning Octave
🤖 MatLab/Octave examples of popular machine learning algorithms with code examples and mathematics being explained
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
Simple machine learning library / 簡單易用的機器學習套件
Vídeos e códigos do Universo Discreto ensinando o fundamental de Machine Learning em Python. Para mais detalhes, acompanhar a playlist listada.
Stock price trend prediction with news sentiment analysis using deep learning
This repository contains all the programming exercises in Python for the Coursera course called "Machine Learning" by Adjunct Professor Andrew Ng at Stanford University.
A learned index structure
Variational Bayes linear and logistic regression
Market Mix Modelling for an eCommerce firm to estimate the impact of various marketing levers on sales
📈 Useful notes and personal collections on statistics.