APMLV ( i.e. Automated Prediction and Management of Logical Volumes ) is a project that leverages deep learning and automation to optimize the management of logical volumes resources

Algorithmic forecasting of energy consumption

This project involves developing and testing a trading model designed to predict stock prices and evaluate trading strategies. The core of the project includes building and training a LSTM based model for time series forecasting in addition to a RL model, evaluating its performance, and visualizing the results.

This Model is Base On Halt & Winter Algorithm.This Model is Forecast About Seasonal Data.

forecasting time series Singapore PSI (pm2.5) 2016-2019

NFV System Supporting Autoscaling of Bare-metal Resource

An implementation of AE LSTM based. We test our architecture on several tasks as reconstructing synthetic time series, s&p 500 stocks, and forecasting s&p 500 stocks based on the decoded information (also known as latent space) features we extract from the AE

This project explores the dynamics of online conversations on Reddit. By comment embeddings and clustering them into discrete states, we model the transitions between these states using higher-order Markov processes offering a clear picture of conversational flow and sentiment dynamics over time.

A plug and play framework for Temporal Fusion Transformer. Predict your future!

StockLLM: A Stock Analyzer with Comprehensive LLM Insights

The random walk application receives a number of steps from the user and simulates a walk in a random direction with equal step sizes (one unit). Following each run, a histogram plots the distances from the origin for each run, and the expected value can be evaluated as the average distance approach a certain value.

This project aims to use LSTM for forecasting the total output of a RAS system based on the sequential input data.

Scripts to build and run WRF and WPS in docker

Runner-up team (2nd place) in AI4VN2022: Air Quality Forcasting Challenge

A combined LSTM and LightGBM framework for improving deterministic and probabilistic wind energy forecasting

weatheril is an unofficial [IMS](https://ims.gov.il) (Israel Meteorological Service) python API wrapper.