Author: Shengxuan Wang
From: Oregon State University
Building Machine Learning model from Scratch, without using any ML package. Only use data processing package, e.g. Pandas and Numpy, and a package I made: Popanda (see the detail here: https://github.com/shawn120/Popanda_Enhance_of_Pandas) Then using some data set to test them.
Models include Linear Regression, Logistic Regression, Perceptron, and Decision Tree.
Crypto-Currency-Predictor This machine-learning algorithm takes in data from the last 60 days and tries to predict tomorrow's price of any crypto you
Horovod Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make dis
Table of contents Extended Isolation Forest Summary Motivation Isolation Forest Extension The Code Installation Requirements Use Citation Releases Ext
Price-Predictor Ml based project which uses regression technique to predict the price. I have used various regression models and finds the model with
Puesta en Producción de un modelo de aprendizaje automático con Flask y Heroku L
Hand Crafted Models Simple linear model implementations from scratch. Table of contents Overview Project Structure Getting started Citing this project
It selects the best indexing parameters to achieve the highest recalls given memory and query speed constraints.
R-Solver A Python tools for deriving R-Type adaptors for Wave Digital Filters. This code is not quite production-ready. If you are interested in contr
CMeans_fuzzy Classification based on Fuzzy Logic(C-Means). Table of Contents About The Project Fuzzy CMeans Algorithm Built With Getting Started Insta
Nixtla Statistical ⚡️ Forecast Lightning fast forecasting with statistical and econometric models StatsForecast offers a collection of widely used uni
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A repository for collating all the resources such as articles, blogs, papers, and books related to Bayesian Statistics.
Bodywork deploys machine learning projects developed in Python, to Kubernetes. It helps you to: serve models as microservices execute batch jobs run r
Somoclu Somoclu is a massively parallel implementation of self-organizing maps. It exploits multicore CPUs, it is able to rely on MPI for distributing
House-Price-Prediction-Using-Linear-Regression The dataset I used for this personal project is from Kaggle uploaded by aariyan panchal. Link of Datase
Dynet A concept I came up which ditches the idea of "layers" in a neural network. Install Copy Dynet.py to your project. Run the example Install matpl
ml4ir: Machine Learning for Information Retrieval | changelog Quickstart → ml4ir Read the Docs | ml4ir pypi | python ReadMe ml4ir is an open source li
Maya: Datetimes for Humans™ Datetimes are very frustrating to work with in Python, especially when dealing with different locales on different systems
High performance Python GLMs with all the features!
PyDLM Welcome to pydlm, a flexible time series modeling library for python. This library is based on the Bayesian dynamic linear model (Harrison and W
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