📚 Solutions to Introduction to Algorithms Third Edition

This project presents a weather-proof model for accurate detection of dogs and cats, streamlined for desktop application. Utilizing renowned models, transfer learning, data augmentation, and weathe…

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…

get BTC price via api and Tell it as a voice

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,…

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 interpret…

An environmental analysis project comparing air pollution levels and factors influencing air quality across diverse global cities.

Predicting the Concrete Compressive Strength Using ML Models

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. …

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 …

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 campai…

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 licens…

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.

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 estimat…

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, achi…

Implementation of Reinforcement Learning Algorithms (From Reinforcement Learning An Introduction By Sutton & Barto)

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 m…

An extensive exploration and preprocessing of Flight data. The project encompasses detailed EDA (Univariate, Bivariate, and Multivariate analysis), along with comprehensive data preprocessing techn…

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 featur…

This repository contains a Python script that retrieves historical EUR/JPY exchange rates from the Twelve Data API and applies an ARIMA (Autoregressive Integrated Moving Average) model to predict f…

In this repository by using Pytorch, I build, train and evaluate LSTM models for predicting Google stock prices

In this repository by using tensorflow, I build, train and evaluate LSTM models for predicting Google stock prices

📈 Constantly summarizing open-source dataset and critical papers in the field of surface defect research which are of great importance.

An Efficient, Scalable and Optimized Python Framework for Deep Forest (2021.2.1)

Repository containing notebooks of my posts on Medium

Keras Implementation of Neural Style Transfer from the paper "A Neural Algorithm of Artistic Style" (http://arxiv.org/abs/1508.06576) in Keras 2.0+

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas …

A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.