AshkanForootan's Stars
FarzadNekouee/Garbage_Classification_ResNet50_Scratch_to_Transfer-Learning
In this project, we harness ResNet50 for garbage classification. Using a dataset pivotal for automating waste segregation, we address challenges like class imbalance with data augmentation and tailored metrics. The journey involves analyzing the dataset, confronting imbalances, and developing models from scratch and via transfer learning.
hamedanchi/instance-segmentation-Mack-RCNN
edris-mala/Medical-cost-personal
FarzadNekouee/Retail_Customer_Segmentation_Recommendation_System
Analyzing and transforming a UK-based retail dataset (2010-2011) into a customer-centric format for customer segmentation using K-means clustering. Implementing a personalized recommendation system to enhance marketing strategies and boost sales.
FarzadNekouee/XGBoost-CatBoost-Employee-Resignation
The project aims to predict employee resignations using XGBoost and CatBoost regressors. It involves extensive EDA, data preprocessing, model building, hyperparameter tuning, and model evaluation. The objective is to help organizations take proactive steps to retain valuable employees and maintain stability.
FarzadNekouee/Hotel_Booking_Cancellation_Prediction
Predictive modeling of hotel booking cancellations. Handling complex data preprocessing, feature engineering, and noise. Evaluating models for high F1-score and analyzing key features for interpretability.
FatemehHabibimoghaddam/Motion-Detection
FarzadNekouee/DCGAN-Photorealistic-Face-Generator
This project leverages DCGANs and the CelebA dataset to create photorealistic, synthetic human faces. The DCGAN model crafts new faces that, although similar to the celebrities in the training set, are completely fabricated. The goal is to produce lifelike 64x64 pixel faces.
SinDeh/Other
SinDeh/Machine-Learning
SinDeh/Professional-Python
SinDeh/Introductory-Python
SinDeh/IBM-Applied-Data-Science-Capstone
FarzadNekouee/Flight-EDA-to-Preprocessing
An extensive exploration and preprocessing of Flight data. The project encompasses detailed EDA (Univariate, Bivariate, and Multivariate analysis), along with comprehensive data preprocessing techniques - missing value treatment, outlier management, categorical encoding, feature scaling, and skewness transformation.
ElhamMahdian/Thompson-sampling
Thompson sampling
FarzadNekouee/Heart_Disease_Prediction
In this repo, we analyze a dataset of heart patient metrics to build a model identifying heart disease risks. We prioritize high recall for comprehensive detection through EDA, preprocessing, and model building. Explore our approach and findings!
FarzadNekouee/Keras-CIFAR10-CNN-Model
An exploration of CIFAR-10 image classification using a CNN model built with Keras. This repository includes training, evaluation, and external image testing to understand model generalization.
FarzadNekouee/Mobile_Price_Range_Classifier
Launching a mobile company to rival giants like Apple & Samsung, we leverage sales data to discern price ranges for mobiles based on features via ML models like SVM, DT, & RF. Not aiming for exact prices, but a strategic price bracket.
FarzadNekouee/Traffic-Violation-Detection
An urban traffic violation detection system using classical image processing techniques. Features include real-time traffic light recognition, adaptive night-time stop line detection, robust license plate extraction, PyTesseract OCR for text recognition, dynamic penalized plate display, and MySQL logging.
FarzadNekouee/Imbalanced_Bank_Loan_Modeling
Classification project to pinpoint potential loan customers from an imbalanced dataset. Emphasizes on penalized and tree-based algorithms, optimizing for both recall and precision to enhance campaign efficacy and conversion rates.
FarzadNekouee/Regression-Assumptions-Regularization
Dive into polynomial regression and its assumptions in car price prediction. This repo explores Linear, Polynomial, Ridge, Lasso, and Elastic-Net models on the CarDekho dataset for accurate estimates. A deep dive into regression and regularization.
MManoochehry/Image-Classification-using-CIFAR-10-dataset
MManoochehry/Mobile-Price-Prediction-Classification
In this project, I analyzed dataset 'train.csv' to predict mobile ‘Price Range’ for dataset 'test.csv'. I performed preprocessing, exploratory data analysis (EDA), and visualized insights. Utilized Decision Trees, Random Forest, and SVM models to predict 'Price Range', allowing analysis of mobile device pricing based on comprehensive features.
MManoochehry/Clustering-Methods-For-Unsupervised-Data
In this project, our goal is to explore various clustering techniques and identify the most suitable method for the given dataset. We implemented K-Means, MiniBatchKMeans, MeanShift, AffinityPropagation, Hierarchical, and DBSCAN, and evaluated their performance using silhouette, Calinski Harabasz, and Davies Bouldin scores.
MManoochehry/Bank-Loan-Classification-Prediction
In this project, I explored a dataset to predict personal loan acceptance. I employed feature engineering techniques and implemented machine learning models, including Logistic Regression, KNN, and Naive Bayes (ComplementNB, MultinomialNB). The goal was to achieve individual's likelihood of accepting a personal loan offer from the bank.
MManoochehry/PCA-Clustering-on-Country-Data
In this project, I analyzed a dataset of socio-economic indicators. After preprocessing & EDA, I used PCA for dimensionality reduction & clustering to identify countries in need of financial aid.
MManoochehry/Linear-Regression
This project uses Linear Regression for car price prediction, implementing advanced techniques such as K-Fold cross-validation, feature selection, and dot product operations. Through careful feature engineering and model evaluation, it delivers accurate selling price predictions for unseen car data.
FarzadNekouee/Gold-Price-Prediction-LSTM
Harnessing LSTM for gold price prediction from 2013-2022. Trained on 9 years of data, the model predicts prices for 2022. The repo contains detailed explorations, visualizations, and insights, achieving high accuracy evaluated by RMSE.
jupyter/jupyter
Jupyter metapackage for installation, docs and chat
jwasham/coding-interview-university
A complete computer science study plan to become a software engineer.