An algorithm that can detect and track the object of interest (OOI) in video frames.

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.

High-precision indoor positioning framework for most wifi-enabled devices.

Determining the housing prices of California properties for new sellers and also for buyers to estimate the profitability of the deal.

Data science practice project from "Hands-On Machine Learning with SciKit-Learn and TensorFlow"

Regression and Classification task with sklearn.

Predict sales prices and practice feature engineering, RFs, and gradient boosting

Kaggle Competition - Analysis and prediction of PUBG players' finishing placement based on their final stats

Machine Learning project for finding Potential of players with FIFA19 database

In this project using New York dataset we will predict the fare price of next trip. The dataset can be downloaded from https://www.kaggle.com/kentonnlp/2014-new-york-city-taxi-trips The dataset contains 2 Crore records and 8 features along with GPS coordinates of pickup and dropoff

Supervised machine learning to predict housing price

A Machine Learning Model that predicts price of pre-owned cars using Linear Regression and Random Forrest Regressor.

🚜 Predict Bulldozers sale price based on their past sales records.

Its a Machine learning project where I used different python libraries like Pandas,Numpy,Matplotlib.At first, I collected data and preprocess the data, training the data and testing the data and finally we predict the percentage chances of affecting the lung cancer based on machine earning Algorithms.

Using Various Regression Algorithms to Predict House Sales

I participated in a Kaggle competition where I used a random forest regressor and hyper-parameter tuned my model to most accurately predict the sale price of a home based on multiple characteristics and features.

This repository contains a Machine Learning Project used to predict the future sale price of a bulldozer, given its characteristics and previous examples of how much similar bulldozers have been sold for.

Goal is to predict the concrete compressive strength using collected data