Dr Ali Asghar Heidari's starred repositories
transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
awesome-open-gpt
Collection of Open Source Projects Related to GPT，GPT相关开源项目合集🚀、精选🔥🔥
mljar-supervised
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
deep-learning-time-series
List of papers, code and experiments using deep learning for time series forecasting
skforecast
Time series forecasting with scikit-learn models
time-series-forecasting-with-python
A use-case focused tutorial for time series forecasting with python
epftoolbox
An open-access benchmark and toolbox for electricity price forecasting
Online-Recurrent-Extreme-Learning-Machine
Online-Recurrent-Extreme-Learning-Machine (OR-ELM) for time-series prediction, implemented in python
automl-in-action-notebooks
Jupyter notebooks for the code samples of the book "Automated Machine Learning in Action"
AI-Ecosystem
This is a collection of AI ecosystem, which gathers and organizes various interesting and useful AI-related projects
kdd2018_air_pollution_prediction
KDD2018 CUP - Predicting air pollutants for next 48 hours in London and Beijing using Deep Learning
The-best-classifier
In this notebook I have tried to use all the classification algorithms that I have learned in Machine Learning with Python course authorized by IBM.
Wind-Speed-Prediction
🍃Wind Speed Prediction Model with LSTM and Tensorflow backend!!!
chatgpt-clone
ChatGPT (Chat Generative Pre-trained Transformer) is a chatbot developed by OpenAI and launched in November 2022. It is built on top of OpenAI's GPT-3 family of large language models and has been fine-tuned (an approach to transfer learning) using both supervised and reinforcement learning techniques.
Ali-Asghar-Heidari
Ali Asghar Heidari has been an Exceptionally Talented Researcher with the School of Computing, National University of Singapore (NUS), University of Tehran, and an elite researcher of Iran’s National Elites Foundation (INEF). He was born in 1989 and has studied information systems as an outstanding ranked one student with several awards from the College of Engineering, University of Tehran. He has been ranked among the top scientists for Computer science prepared by Guide2Research (https://www.guide2research.com/u/ali-asghar-heidari), the best portal for computer science research, as an outstanding researcher with an impressive record of cooperation on many international research projects with different top researchers from the optimization and artificial intelligence community. He has been ranked in the world’s top 2% scientists list of Stanford University, and Publons has recognized him as the top 1% peer reviewer in computer science and cross-field because he has reviewed more than 350 ISI papers for top journals he published on them. He has authored more than 110 research articles with over 6300 citations (i10-index of 74 and H-index of 44) in prestigious international journals, such as IEEE internet of thing, IEEE Transactions on Industrial Informatics, Information Fusion, Information Sciences, Future Generation Computer Systems, Renewable, and Sustainable Energy Reviews, Energy, Cleaner Production, Energy Reports, Energy Conversion and Management, Applied Soft Computing, Knowledge-Based Systems, IEEE Access, and Expert Systems with Applications. He has several highly cited and hot cited articles. His research interests include performance optimization, advanced machine learning, evolutionary computation, optimization, prediction, solar energy, information systems, and mathematical modeling. He was the second top reviewer and “outstanding reviewer” of applied soft computing journal in 2018. For more information, researchers can refer to his website https://aliasgharheidari.com.
DALL-E-CLONE
AI image generator, using openai DALL-E API 🎉
AirQuality-TimeSeriesForecasting
Citation: http://dx.doi.org/10.1016/j.snb.2007.09.060 & Dataset repository: https://archive.ics.uci.edu/ml/datasets/Air+quality
Time-Series-Analysis-of-Air-Quality-Data
This work aims to analyze the air quality in India and the effects of seasons and COVID-19 on the concentration of pollutants in the air and thereby their effect on the air quality index (AQI). The analysis is performed on a full scale, taking into consideration different levels of granularities such as daily, weekly and monthly data. This study performs extensive preprocessing of the time series data for air quality to make it output the best results. The results evidenced that particulate matter i.e., PM 2.5 and PM 10 have the greatest impact on air quality. Analysis of the effect of change in seasons on the overall air quality has been carried out, along with the impact of the nationwide lockdown due to COVID-19, which led to a substantial improvement in the AQI levels. Furthermore, we also use the state-of-the-art forecasting algorithm Prophet to predict the monthly average air quality index and compare it with the actual recorded values, giving us a highly accurate prediction. We also performed a comparative analysis of AQI for the cities of Delhi and Bengaluru, having different seasons and climates, which results in valuable insights on to what extent the environmental factors affect the air quality measures of that location.
Air-Pollution-Data-Prediction
All the codes for the air pollution data prediction
Air-Pollution-Prediction
Air Pollution Prediction
Air_Pollution_Prediction_ML_DL
Air pollution prediction