Building an AI Driven Portfolio Management System: From Machine Learning Basics to Advanced Implementation

Two important architectures are Artificial Neural Networks and Long Short-Term Memory networks. LSTM networks are especially useful for financial applications because they are designed to work with ...
The Print

Leveraging AI and Machine Learning for Intelligent Portfolio Management

Artificial intelligence and machine learning are reshaping how investors build and maintain portfolios. These tools bring ...
GitHub

mohansree14/Bayesian-Deep-Learning-for-Probabilistic-Financial-Forecasting

This project implements state-of-the-art deep learning models for financial time series forecasting with a focus on uncertainty quantification. The system provides not just point predictions, but ...
GitHub

Chinese sentence level sentiment analysis

The results report the highest accuracy and the mean accuracy of 10 times running respectively. The Bi-LSTM consists of 3 bidirectional LSTM layers, while the RCNN achieves the results with only 1 ...
Analytics Insight

10 Innovative Keras Project Ideas with Source Code for 2025

Overview: Keras remains one of the most intuitive and developer-friendly frameworks for building deep learning models, making ...
IEEE

Fine-Tuning of Predictive Models CNN-LSTM and CONV-LSTM for Nowcasting PM

Abstract: Particulate matter forecasting is fundamental for early warning and controlling air pollution, especially PM2.5. The increase in this level of concentration will lead to a negative impact on ...
IEEE

Channel Estimation Using CNN-LSTM in RIS-NOMA Assisted 6G Network

Abstract: The combination of non-orthogonal multiple access (NOMA) and reconfigurable intelligent surface (RIS) technologies is proposed to meet the demands of data rate, latency, and connectivity in ...