🚀 Optimizing the Elliott Wave Theory using genetic algorithms to forecast the financial markets.

Source Code Automated Refactoring Toolkit

Perform statistics on Mixpanel API data

Conditional Associative Logic Memory

ALGORITHM TRADING AND STOCK PREDICTION USING MACHINE LEARNING

天池项目：新浪微博互动预测

Regression Error Characteristic (REC) Curves in Python

A Flask web application to scrape and analysis Amazon Reviews

FIFA Overall Player Ratings Prediction Using Regression Methods

Basit Regresyon: Python ile Uygulama

This repository focuses on two machine learning projects in the healthcare domain.

Solar Irradiance Prediction using PySpark

Provides methods to automate the Gender Pay Gap analysis. It performs the exploratory data analysis and data modeling to obtain the Salary Gap Decomposition, the Adjusted Gender Pay Gap and the significant variable coefficients.

regression-based waveform estimation analysis of Delogu, Brouwer, and Crocker (2019, Brain and Cognition)

Interface machine learning with Cosmology and General Theory of relativity to visually analyze the evolution of GRS 1915+105 Black hole X-ray binary using WATCH ASM data captured aboard GRANAT.

Code to analyze diverse data and predict wind velocity with tensorflow. It employs a neural network architecture to train and optimize the model for regression problems.

Python functions for numerical analysis: numerical schemes for ODEs, linear algebra, linear/non-linear/iterative solvers, interpolation, and regression analysis.

The objective of this mini-project is to Recover a full image from a small number of sampled pixels (compressed sensing). Although the primary goal of this project is to understand and explore the application of regularized. In the process of recovering image pixel using regularized regression, we will explore different concepts and their unders…

This is a tool for testing the PUF against Modelling attack

By clustering data into 88 car respondents and 88 bicycle respondents, a measure of people’s willingness to shift to environment friendly choices like cycling using econometric tools and examining how much are car users willing to pay to shift to cycling .