pca-analysis

UnSupervised and Semi-Supervise Anomaly Detection / IsolationForest / KernelPCA Detection / ADOA / etc.

Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch

Includes top ten must know machine learning methods with R.

system performance characterization tool based on linux perf

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.

PCA and DBSCAN based anomaly and outlier detection method for time series data.

Science des Données Saison 2: Exploration statistique multidimensionnelle, ACP, AFC, AFD, Classification non supervisée

This repository contains the code and datasets for creating the machine learning models in the research paper titled "Time-series forecasting of Bitcoin prices using high-dimensional features: a machine learning approach"

This program allow you to extract some features from pcap files.

The project aimed to implement Deep NN / RNN based solution in order to develop flexible methods that are able to adaptively fillin, backfill, and predict time-series using a large number of heterogeneous training datasets.

Dimensionality reduction

Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"

Karma of Humans is AI

Predicting solar energy using machine learning (LSTM, PCA, boosting). This is our CS 229 project from autumn 2017. Report and poster are included.

CUDA C implementation of Principal Component Analysis (PCA) through Singular Value Decomposition (SVD) using a highly parallelisable version of the Jacobi eigenvalue algorithm.

A comprehensive approach for stock trading implemented using Neural Network and Reinforcement Learning separately.

This repo contains auto encoders and decoders using keras and tensor flow. It shows the exact encoding and decoding with the code part.

Implementations of machine learning algorithm by Python 3

2020 Spring Fudan University Data Mining Course HW by prof. Zhu Xuening. 复旦大学大数据学院2020年春季课程-数据挖掘（DATA620007）包含数据挖掘算法模型：Linear Regression Model、Logistic Regression Model、Linear Discriminant Analysis、K-Nearest Neighbour、Naive Bayes Classifier、Decision Tree Model、AdaBoost、Gradient Boosting Decision Tree(GBDT)、XGBoost、Random Forest Model、Support Vector Machine、Principal Component Analysis(PCA)