18 Projects in AI & ML

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.

Austin Housing Price Predictions is a start-to-finish regression project which includes image processing, NLP, Neural Networks, transfer learning, and model ensembling.

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

A Predictive Model for Marketing Campaigns

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.

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

Recommender Systems 2021/2022: Content Based Recommenders Project

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.

Train a Smartcab to Drive

Predicting Boston Housing Prices

This Repository contains the projects which are part of Udacity Machine Learning Nanodegree

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.

پخش زنده پیرامون برخی اصطلاحات و مشکلات در یادگیری ماشین و یادگیری عمیق

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)

Predicting potential donors using various machine learning models for Charity

Applying AI to medical use cases: Diagnoses of lung and brain disorders, Building risk models and survival estimators for heart disease via RF, and Using NLP to extract information from radiology reports.