Applied reinforcement learning to build a simulated vehicle navigation agent. This project involved modeling a complex control problem in terms of limited available inputs, and designing a scheme to automatically learn an optimal driving strategy based on rewards and penalties.

Machine learning prediction project, R studio, 2019.

I used this notebook to discuss different supervised learning approaches. In the notebook you can find evaluations of a logistic regression, a K-Nearest-Neighboor, a Support Vector Machine, a Decision Tree and the ensemble methods Random Forest, AdaBoost and XGBoost Classifyer.

in this repo, you will find implementation of various classification models, data augmantation ,cnn designing and model reguralization

I have developed a GitHub project on ex-showroom car price prediction. The project includes data cleaning, data modeling, and data selection for accurate predictions. It also involves feature selection, model evaluation, testing, and comparison to determine the most effective model.

A project featuring use of statistical techniques for exploratory data analysis and data mining techniques for predicting the quality of wine. 🍷🍸🍹

Applying Supervised learning techniques on data to help CharityML identify people most likely to donate to their cause.

Built an algorithm to identify canine breed given an image of a dog. If given image of a human, the algorithm identifies a resembling dog breed.

This linear regression model tuning is an exercise for a Data Science Online Bootcamp.

Recommender Systems 2021/2022: Content Based Recommenders Project

Train a Smartcab to Drive

Predicting Boston Housing Prices

Sameer Girolkar's AIML practice Notebooks

In this project, I use several different classification algorithms to predict whether a patient has breast cancer or not. This project uses K-fold cross validation, logistic regression, LDA, QDA, SVM, and model tuning techniques to achieve a 96% accuracy rate. This project was completed via R Markdown and LaTex.

This is the historical data that covers sales of a supermarket, Walmart. In this work, I tried to explore the dataset and create a simple model to predict the sales (Weekly_Sales)

In this project we're going to explore a workflow to easily compete in the Kaggle Titanic competition, using a pipeline of functions to reduce the number of dimensions you need to focus on.

Applied reinforcement learning to build a simulated vehicle navigation agent. This project involved modeling a complex control problem in terms of limited available inputs, and designing a scheme to automatically learn an optimal driving strategy based on rewards and penalties.

The Office of Foreign Labor Certification is facing a dramatic increase in work visa applications, but is hampered by a sluggish review system. It needs to improve the process by developing a way to quickly, accurately identify applications likely to be accepted or rejected so their processing may be prioritized.

Recommender Systems 2021/2022: Neural Network Recommenders Project

The folliwing ML project involves EDA analysis of Election Dataset, Data preparation for modelling, and prediction using ML models. Also Text Analysis on the inaugral corpora from nltk to analyse the most frequently used words in Presidents' Speeches.