Jiven-Chana
I’m a Maths and Computer Science student at the University of Birmingham with a deep interest in quantitative finance, AI and algorithmic trading.
Pinned Repositories
AdvancedNewsClassifier
A Java-based system that processes news articles using GloVe embeddings and machine learning. It preprocesses text, generates document-level embeddings, and trains a model to classify news articles into categories, using NLP techniques like tokenization, lemmatization, and stop-word removal.
StockLSTMAnalyser
A Java-based tool using LSTM (Deeplearning4j) to predict stock prices. It preprocesses historical data with technical indicators and MinMax scaling, splits data into training and validation sets, trains a 150-unit LSTM model over 30 epochs, and visualizes predicted vs. actual prices.
Concurrent-Firewall-Rule-Management-System
a concurrent firewall management system built with a client-server architecture. It allows real-time configuration and management of firewall rules over a network. The server handles requests to add, list, validate, and delete firewall rules, while tracking IP addresses and ports that match these rules. Also maintains complete log of all requests
Jiven-Chana's Repositories
Jiven-Chana/Concurrent-Firewall-Rule-Management-System
a concurrent firewall management system built with a client-server architecture. It allows real-time configuration and management of firewall rules over a network. The server handles requests to add, list, validate, and delete firewall rules, while tracking IP addresses and ports that match these rules. Also maintains complete log of all requests
Jiven-Chana/StockLSTMAnalyser
A Java-based tool using LSTM (Deeplearning4j) to predict stock prices. It preprocesses historical data with technical indicators and MinMax scaling, splits data into training and validation sets, trains a 150-unit LSTM model over 30 epochs, and visualizes predicted vs. actual prices.
Jiven-Chana/AdvancedNewsClassifier
A Java-based system that processes news articles using GloVe embeddings and machine learning. It preprocesses text, generates document-level embeddings, and trains a model to classify news articles into categories, using NLP techniques like tokenization, lemmatization, and stop-word removal.