Machine Learning C++

Linear Regression From Scratch

In this project, I applied different regression models for rmse and mae on antenna dataset for predict signal strength.

Stock Prediction using LSTM, Linear Regression, ARIMA and GARCH models. Hyperparameter Optimization using Optuna framework for LSTM variants.

Stock Market Forecasting with CoreML in Swift

Implementation of Linear regression on Boston House Pricing and Diabetes data sets using python.

A set of projects I worked on as part of my PG Diploma in Data Science Program

This repository contains our project on Stock Market Price prediction Using Historical Data

Open Deep Learning and Reinforcement Learning lectures from top Universities like Stanford University, MIT, UC Berkeley. And an intent classifier which can classifies a query into one of the 21 given intents.

Stock prediction model with data imported from quandl

Apache Spark machine learning project using pyspark

Dummy variables can be really helpful while creating multiple linear regression models.

In this project I have implemented 14 different types of regression algorithms including Linear Regression, KNN Regressor, Decision Tree Regressor, RandomForest Regressor, XGBoost, CatBoost., LightGBM, etc. Along with it I have also performed Hyper Paramter Optimization & Cross Validation.

This is Flask integrated Machine Learning model which uses Linear Regression to Predict the CO2 Emission of Vehicle

Simple regression problem where by pre-loaded data I have shown different regression algorithm and their performance on data.

Few linear regression models developed by me.

The objective is to build a ML-based solution (linear regression model) to develop a dynamic pricing strategy for used and refurbished smartphones, identifying factors that significantly influence it.

Machine Learning Lecture Notes