🔮Trying to find the best movie to watch on Netflix can be a daunting. Case Study for Recommendation System of movies in Netflix.🔧

Self Driving Car Project 6 - Sensor Fusion(Extended Kalman Filter)

Compare the quality between two images using RMSE, SSIM, and PSNR. (part of I3D 2018 Montage4D.com)

missCompare R package - intuitive missing data imputation framework

A hyperopt wrapper - simplifying hyperparameter tuning with Scikit-learn style estimators.

A framework of PERformance METRICS (PerMetrics) for artificial intelligence models

Soybean, CBOT Soybean Futures + (2015 USA Weather Avg, Max, Min by USDA-NASS-soybeans-production_bushels-2015)

Building a model which can predict the number of online 'shares' an article will get based on a set of variables attached to it. (Python)

Multiple randomized ANN are being generated that is being taken from user input(total number of ANN) then we have approached one of the nature-inspired-algorithms such as DIFFERENTIAL-EVOLUTION(DE) on a soil-content-dataset to prove that it has better prediction and optimising values other than some well defined algorithms such as SUPPORT-VECTOR-REGRESSION(SVR) and MLP-REGRESSOR.

Posts/Feeds recommendation engine based on content based and collaborative filtering methods

Implementing the extended Kalman filter in C++ for Self Driving cars.

Sensor Fusion: Unscented Kalman Filter, LiDAR&RADAR

A recommendation system for Restaurants!

Unscented Kalman Filter that estimates the location of a moving object via Radar and Lidar sensor fusion

Implementing the Unscented Kalman filter in C++ for Self Driving cars.

Applied Least Square, Ridge and Lasso regression models to predict the number of comments a blog post will receive

🏎️ Extended Kalman Filter (EKF) Localization Project using C++ and Eigen library for the Self-Driving Car Nanodegree at Udacity

In this repository, I have worked out in one of the Kaggle Competition Data, "Predict Future Sales". I have used XGBoostRegressor. I have also used Fastai API for Feature Preprocessing to enhance the Model accuracy. You can get insights about Fastai Implementation as well.

The objective of this project is to predict the prevailing wage that is at optimum.

An R package to apply affine and similarity transformations on vector layers (sp objects)

Code for the Elo Merchant Category Recommendation Kaggle challenge

Understanding Trends in Football Transfers and trying to build a prediction model to predict the market value of players.

Udacity Self Driving Car Engineer Project - Unscented Kalman Filter & Sensor Fusion. See src/ukf.cpp and src/tools.cpp for my solution..

implement an unscented Kalman filter using the CTRV motion model. the results is comparable with my EKF project repo.

Utilized a Kalman Filter to estimate the state of a moving object of interest with noise

🏎️ Unscented Kalman Filter (UKF) Localization Project using C++ and Eigen library for the Self-Driving Car Nanodegree at Udacity

Analyzed a Google Merchandise Store customer dataset to predict revenue per customer (also known as GStore, where Google swag is sold)

Data Analysis and Prediction of New York Taxi Trip Duration Using Machine Learning Models

Term 2 Project 7 - Self Driving Car Nano Degree Proram, Unscented Kalman Filter

Using Root Mean Squared Error to evaluate performace of Kalman Filter