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ames_housing_data_processing

ann-churnmodelling

This code demonstrates the basic end-to-end workflow of developing, training, and evaluating a deep artificial neural network classifier on a real-world classification problem involving preprocessing of categorical variables.

cia_country_analysis_kmeans_clustering

color_quantization_kmeans_clustering

fandango_movieratings

fraud_detection_with_som

project offers a practical application of machine learning and SOMs for fraud detection, which can be crucial for financial institutions.

google_stock_price_lstm

This project addressed the problem of forecasting future stock prices based on historical data using machine learning.

hierarchical_clustering_on_vehicledataset

image_classification_with_cnn

The "Image Classification with Convolutional Neural Networks (CNN)" project is a demonstration of leveraging deep learning, specifically Convolutional Neural Networks, to classify images. In this project, a CNN is trained to distinguish between cats and dogs, showcasing the power of deep learning in computer vision tasks.

lfbnet

This repository implements a robust deep learning method (LFBNet) for medical image segmentation using a two systems approach. Learning fast and slow strategy for robust medical image analysis.

marketing_campaigns_kmeans

ml-detecting-mines-knn

ml-from-scratch

In this Repository, I have implemented multiple ML algorithms from scratch. Please feel free to share or comment.

ml-from-scratch-kmeans

This project demonstrates the implementation of the K-Means clustering algorithm in Python without relying on external libraries.

ml-from-scratch-knn

The implementation of the KNN classifier model built entirely from scratch without machine learning libraries, only using NumPy

ml-from-scratch-naive-bayes

Develop a Naive Bayes classifier for classification problems without using external ML libraries.

ml-from-scratch-random-forest

This implementation builds the random forest classifier from scratch without using scikit-learn or other ML libraries, relying only on NumPy.

ml-from-scratch-svm

The code implements the core math behind a linear SVM classifier. The only library used is scikit-learn for data generation, the SVM logic is implemented from scratch to better understand the algorithm.

ml-linear-regression

ml-logistic-regression-project

movie_recommendation_with_sae

This project highlights the application of deep learning in the development of recommendation systems and showcases the capabilities of Stacked Autoencoders in understanding and predicting user preferences

pca-cancer-diagnostic--handwritinganalysis

recommender_system_with_rbm

This project showcases the practical application of deep learning in the field of recommendation systems, providing valuable experience in the development and evaluation of AI-driven solutions for personalized content recommendations.

rezakhosravi72.github.io

rezz

sql-project

sql-project-car-records

tableau_projects

Tableau Projects with Real-World Datasets

walmart_sales_data_analysis

wholesome_customers_clustering_dbscan