regression-analysis

Test/benchmark regression and comparison system with dashboard

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

Data science investigations into the mechanics of the world's greatest role playing game

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.

Basic statistical modelling examples.

Implementation of a Partial Least Squares Regressor

Football player rating analysis and position recommendation

Conditional Associative Logic Memory

Perform statistics on Mixpanel API data

A Software to interactively edit data in a graphical manner

Java·Applied·Geodesy·3D - Least-Squares Adjustment Software for Geodetic Sciences

Fast estimation of generalized linear models with high dimensional categorical variables in Julia

Using Machine Learning Algorithms for Regression Analysis to predict the sales pattern and Using Data Analysis and Data Visualizations to Support it.

Predicting the stock market opening values using Deep learning's Model Recurrent Neural Networks which is a very powerful model.

ALGORITHM TRADING AND STOCK PREDICTION USING MACHINE LEARNING

Source Code Automated Refactoring Toolkit

Visual regression testing made easy. Automating the boring stuff

Julia's HPC command for automatic feature/model selection using all-subset-regression approaches

The main aim of this project is to tell that the certain project will be successful or it will fail by applying machine learning algorithm. In this , LOGISTIC REGRESSION is used to determine the success of the project by splitting the data into training and testing models and predicting a successful one.

🚗 Solving the problem of predicting the price of a used car using Sklearn's supervised machine learning techniques.

Performing the Financial Analysis on Historic Stock Market Data such as calculating various risks, returns,etc.

A Linear Regression model to predict the car prices for the U.S market to help a new entrant understand important pricing variables in the U.S automobile industry. A highly comprehensive analysis with detailed explanation of all steps; data cleaning, exploration, visualization, feature selection, model building, evaluation & MLR assumptions validity.

It is from a kaggle competition where we have to predict the future sales using Machine Learning or Deep Learning. It is a Advanced Regression Problem where Statistics and time series analysis is also required. This problem can be very well done by Deep Learning's Model Recurrent Neural Networks.

Sensor data of a renowned power plant has given by a reliable source to forecast some feature. Initially the work has done with KNIME software. Now the goal is to do the prediction/forecasting with machine learning. The idea is to check the result of forecast with univariate and multivariate time series data. Regression method, Statistical method.

My Code Repository for Coursera Data Science Specialization by John Hopkins University

Winning solution of the Kaggle KDD BR 2018 machine learning competition

Predicting Prices for the products to be sold on Black Friday in US using Regression Analysis, Feature Engineering, Feature Selection, Feature Extraction and Data analysis - Data Visualizations.

Implementing a Gaussian Process regression model from scratch

Linear Regression Analysis on Wine data - Pre-processing data, Exploratory Data Analysis, Building a model, Check assumptions, Goodness of fit and Compare with different methods.

It is a Competition for Regression Challenge held by Kaggle, It is based on a Avito Dataset whose size is 123GB which can be accessed from Kaggle, I have done Data Pre-processing, feature engineering, feature extraction, data visualization, machine learning, stacking and boosting