This is the Study Guide for Learn Machine Learning in 3 Months (PyTorch Curriculum) by Siraj Raval on Youtube

This is the code for "ChatGPT in 5 Minutes" By Siraj Raval on Youtube

This is the code for "AI in Finance" By Siraj Raval on Youtube

Sources codes for: Mastering Python for Finance, Second Edition

An algorithm for robot navigation was designed, accounting for random obstacles and determining optimal paths. It leverages a genetic algorithm to pinpoint the shortest route from start to end.

A hybrid approach was developed to predict NASA website queries using neural networks and metaheuristic optimization algorithms. The weights of the model was optimized using GWO, PSO, and ICA, harn…

In 2021, a precise forecast of Iran Post's 2021-2022 income was achieved using ARIMA, with only a 1.5\% error. This approach was subsequently extended to estimate the income and traffic for 2022-2023.

Developed a Windows tool using PyQt5, integrating K-means clustering for data analysis. The application recommends optimal cluster numbers, identifies cluster members, and allows exporting results …

Developed a Windows-based app for analyzing data distributions and identifying the best-fitted distribution using the Maximum Likelihood Estimation algorithm. The app features histogram analysis, e…

Projects with Genetic Algorithm (GA), Ant Colony Optimization (ACO), and Particle Swarm Optimization (PSO)

Implemented a CNN-LSTM Action Recognizer for dynamic motion analysis, integrating convolutional and recurrent neural networks to efficiently recognize and classify actions in video data of UCF101 d…

Developed a custom application of the Segment Anything Model (SAM) for breast cancer tissue segmentation, utilizing Hugging Face's Transformers and fine-tuning the decoder to predict segmentation m…

Using DIgSILENT, a smart-grid case study was designed for data collection, followed by feature extraction using FFT and DWT. Post-extraction, feature selection. CNN-based and extensive machine lear…

Developed the ViViT model for medical video classification, enhancing 3D organ image analysis using transformer-based architectures.

ADHDeepNet is a model that integrates temporal and spatial characterization, attention modules, and explainability techniques, optimized for EEG data ADAD diagnosis. Neural Architecture Search (NAS…

A 3D Attention U-Net model is developed, aimed at segmenting and tracking Multiple Sclerosis lesions in MRI images.

Developed an AI-driven project for Printed Circuit Board (PCB) analysis, incorporating computer vision for image registration, IC detection, and recognition, along with web scraping for data extrac…

Developed BERT, LSTM, TFIDF, and Word2Vec models to analyze social media data, extracting service aspects and sentiments from a custom dataset. Provided actionable insights to telecom operators for…

Developed a reinforcement learning framework using Deep Q-Networks (DQN) to optimize scheduling in Wireless Sensor Networks (WSN), enhancing energy efficiency and state estimation through a custom …