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.
Short PhD seminar on Machine Learning Security (Adversarial Machine Learning)
The project's goal is to show a real world application of image segmentation using k means algorithm
hgboost is short for Hyperoptimized Gradient Boosting and is a python package for hyperparameter optimization for xgboost, catboost and lightboost using cross-validation, and evaluating the results o
PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural ne
Time-series-momentum Time-series momentum strategy. You can use the data_analysis.py file to find out the best trigger and window for a given asset an
NCVX (NonConVeX): A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning.
HH-VAEM This repository contains the official Pytorch implementation of the Hierarchical Hamiltonian VAE for Mixed-type Data (HH-VAEM) model and the s
SLAM-application: installation and test (3D): LeGO-LOAM, LIO-SAM, and LVI-SAM Tested on Quadruped robot in Gazebo ● Results: video, video2 Requirement
Pandas Machine Learning and Quant Finance Library Collection
Deepdream Eyes Made in collaboration with Chris George for Art + ML Spring 2019.
auto-sklearn auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. Find the documentation here
BalancingGroups Code to replicate the experimental results from Simple data balancing baselines achieve competitive worst-group-accuracy. Replicating
Linear regression for data with measurement errors and intrinsic scatter (BCES) Python module for performing robust linear regression on (X,Y) data po
Using python and scikit-learn to make stock predictions
luminol Overview Luminol is a light weight python library for time series data analysis. The two major functionalities it supports are anomaly detecti
Federal University of Rio Grande do Norte Technology Center Department of Computer Engineering and Automation Machine Learning Based Systems Design Re
Pyomo is a Python-based open-source software package that supports a diverse set of optimization capabilities for formulating and analyzing optimization models. Pyomo can be used to define symbolic p
Sleep stages are classified with the help of ML. We have used 4 different ML algorithms (SVM, KNN, RF, NN) to demonstrate them.
GluonTS - Probabilistic Time Series Modeling in Python GluonTS is a Python toolkit for probabilistic time series modeling, built around Apache MXNet (
Neighbourhood Retrieval with Distance Correlation Assign Pseudo class labels to datapoints in the latent space. NNDC is a slim wrapper around FAISS. N
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