105 Open source projects that are alternatives of or similar to regression-wasm

A simple machine learning framework written in Swift 🤖

HighCharts demo of scatter plot, including a trend line

Python implementation of Andrew Ng's ML course projects

Code for Java Deep Learning Cookbook

100 Days of ML Coding

My Portfolio

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

a collection of modern sparse (regularized) linear regression algorithms.

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

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。

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

Code for Tensorflow Machine Learning Cookbook

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

A New, Interactive Approach to Learning Python

整理记录本人担任课程助教设计的四个机器学习实验，主要涉及简单的线性回归、朴素贝叶斯分类器、支持向量机、CNN做文本分类。内附实验指导书、讲解PPT、参考代码，欢迎各位码友讨论交流。

machine learning algorithm

Call Open Policy Agent (OPA) policies in WASM (Web Assembly) from .NET Core

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

📦 BRoadly Useful Convenient and Efficient R functions that BRing Users Concise and Elegant R data analyses.

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

Bare bone examples of machine learning in TensorFlow

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

Mathematical & Statistical topics to perform statistical analysis and tests; Linear Regression, Probability Theory, Monte Carlo Simulation, Statistical Sampling, Bootstrapping, Dimensionality reduction techniques (PCA, FA, CCA), Imputation techniques, Statistical Tests (Kolmogorov Smirnov), Robust Estimators (FastMCD) and more in Python and R.

Tracking, notes and programming snippets while learning predictive analytics

Launch machine learning models into production using flask, docker etc.

Aulas da Escola de Inteligência Artificial de São Paulo

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

A simple implementation of the LOESS algorithm using numpy

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

Python module for performing linear regression for data with measurement errors and intrinsic scatter

Starter code of Prof. Andrew Ng's machine learning MOOC in R statistical language

Homomorphic Encryption for TypeScript or JavaScript - Microsoft SEAL

My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge.

Matlab library for gradient descent algorithms: Version 1.0.1

Machine Learning Concepts with Concepts

🌎 I created this repository for educational purposes. It will host a number of projects as part of the process .

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

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

🙄 Difficult algorithm, Simple code.

Lesson material on data science and machine learning topics/concepts

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.

Basic Machine Learning implementation with python

Deep Learning From Scratch

Pure Javascript manually written 👌 implementation of BLAS, Many numerical software applications use BLAS computations, including Armadillo, LAPACK, LINPACK, GNU Octave, Mathematica, MATLAB, NumPy, R, and Julia.

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

15+ Machine/Deep Learning Projects in Ipython Notebooks

For extensive instructor led learning

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

A set of machine learning experiments in Clojure

An introductory statistics course for social scientists, using Stata

⭐️ Univariate Linear Regression with Gradient Descent in JavaScript (Vectorized)

Linear Prediction Model with Automated Feature Engineering and Selection Capabilities

gesture recognition toolkit

Benchmarking and Visualization Toolkit for Penalized Cox Models

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

Machine Learning Procedures and Functions for Neo4j

A MATLAB toolbox for classifier: Version 1.0.7

Set up Seed app and start dev server by running one command

SecMML: Secure MPC(multi-party computation) Machine Learning Framework

A day to day plan for this challenge. Covers both theoritical and practical aspects