Official repo of the article: Yousef, W. A., Ibrahime, O. M., Madbouly, T. M., & Mahmoud, M. A. (2019), "Learning meters of arabic and english poems with recurrent neural networks: a step forward for language understanding and synthesis", arXiv preprint arXiv:1905.05700

handwritten word recognition with IAM dataset using CNN-Bi-LSTM and Bi-GRU implementation.

Powerful XRP price forecasting using public data. Stacking ensemble (Bi-GRU/LSTM/CNN-LSTM + LightGBM/XGBoost, RidgeR). Fuses market OHLCV (CCXT), news sentiment & top50 whale activity. No API keys or signups. Easy setup. CPU/GPU-ready. Multi-horizon single run forecasting. Backtests + Predictions visuals: plot_charts & in-depth tensorboard dash

An AI-powered legal assistant designed to assist with legal queries using a RAG pipeline containing pretrained inLegalBERT model embeddings and a FAISS index trained on the Indian Penal Code (IPC). Gemini answers your queries and provides explanations based on RAG as well. It features a chatbot, judgement prediction and legal document generation.

This paper consists of all source codes related to the paper "An Efficient Framework for Vietnamese Sentiment Analysis", SOMET 2020.

Implementation of CNN and bi-GRU in parallel to solve text classification. In this particular example, I and my colleague, Ida Novindasari, use the AG news dataset from torchtext.datasets.

Given 10 predefined relations like cause-effect, product-producer, etc., the goal was to define the relation and the direction of the relation between 2 entities in a sentence.

⚖️ AskLegal.ai is an advanced AI-powered tool designed to help with legal queries, court cases, and lawsuits. Trained on the Indian Penal Code (IPC) and real case documents, this assistant offers accurate, context-aware responses

Stroke diagnosis

A comparison of different machine learning models for hate speech detection. Trained on a twitter hate speech dataset with more than 25K records.

This project predicts AC.PA stock prices using deep learning. Among the models tested, LSTM + SVR performed best, followed by BiGRU + LSTM. GAN + Transformer underperformed due to instability, highlighting the strength of hybrid sequential models for financial forecasting.

Sentimen Analytics