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.
Apache SINGA Distributed deep learning system http://singa.apache.org Quick Start Installation Examples Issues JIRA tickets Code Analysis: Mailing Lis
Relating-Social-Media-to-Stock-Movement-Public - We explore the application of Machine Learning for predicting the return of the stock by using the information of stock returns. A trading strategy ba
Machine-Learning with python (jupyter) 머신러닝 야학 작심 10일과 쥬피터 노트북 기반 데이터 사이언스 시작 들어가기전 https://nbviewer.org/ 페이지를 통해서 쥬피터 노트북 내용을 볼 수 있다. 위 페이지에서 현재 레포 기
KU AIRS: SPARK Autonomous Vehicle Project Check this link for the blog post describing this project and the video of SPARK in simulation and on parkou
I have collected data about a set of patients, all of whom suffered from the same illness. During their course of treatment, each patient responded to one of 5 medications, Drug A, Drug B, Drug c, Dr
DistortionML Machine Learning approach for quantifying detector distortion fields. This project is a feasibility study for training a surrogate model
Implemented four supervised learning Machine Learning algorithms from an algorithmic family called Classification and Regression Trees (CARTs), details see README_Report.
END TO END MACHINE LEARNING PROJECT ON HITTERS DATASET Can a machine learning project be implemented to estimate the salaries of baseball players whos
OptaPy is an AI constraint solver for Python to optimize the Vehicle Routing Problem, Employee Rostering, Maintenance Scheduling, Task Assignment, School Timetabling, Cloud Optimization, Conference S
XGBoost-Ray is a distributed backend for XGBoost, built on top of distributed computing framework Ray.
DEAP DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data stru
The code from the Machine Learning Bookcamp book and a free course based on the book
Maya: Datetimes for Humans™ Datetimes are very frustrating to work with in Python, especially when dealing with different locales on different systems
CyLP CyLP is a Python interface to COIN-OR’s Linear and mixed-integer program solvers (CLP, CBC, and CGL). CyLP’s unique feature is that you can use i
YouTube Spam Detection This code deletes spam comment on youtube videos based on two characteristics (currently) If the author of the comment has a se
Machine Learning from Scratch Author: Shengxuan Wang From: Oregon State University Content: Building Machine Learning model from Scratch, without usin
dlib C++ library Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real worl
vortex-particles-method-2d vortex particles for simulating smoke in 2d -vortexparticles_s
River is a Python library for online machine learning. It is the result of a merger between creme and scikit-multiflow. River's ambition is to be the go-to library for doing machine learning on strea
Logistic_Regression_Model A logistic regression model for health insurance purchasing prediction This code is using these packages, so please make sur
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