arshidali84,Arshid Ali,github

Interested to Work in the Field of Machine Learning, Power Systems and Research

🔭 I’m currently working on 30-Ready-ML-Projects, a comprehensive repository showcasing practical machine learning applications across diverse domains, including smart grid and energy management.
👯 My main research focus is on ML|DL|RL projects related to power and energy systems by learning Smart circuit breakers to avoid power system blackouts during natural disasters.
🌱 I’m diving deep into Reinforcement Learning, exploring its applications in optimizing energy distribution within smart grids, ensuring efficiency and sustainability.
👨‍💻 My projects span various applications in Machine Learning, Smart Grids, and Energy Management. Find them at My GitHub Profile.
💬 Curious about Machine Learning, Smart Grids, and Energy Management? I'm passionate about discussing innovations and challenges in these fields.
📫 Reach out to me at [email protected] for collaborations, discussions, or inquiries.

Key Areas of Expertise:

Languages and Tools:

I leverage a comprehensive set of machine learning libraries such as TensorFlow, PyTorch, Scikit-learn, Keras, NumPy, Pandas, Matplotlib, SciPy, and PyPI to build and deploy predictive models. These models are specifically designed for optimizing smart grid functionalities, energy forecasting, and anomaly detection within power systems.

Relevant Projects and Contributions:

1. Smart Grid Optimization using Reinforcement Learning:

Implementation of a Reinforcement Learning model for optimal energy distribution within smart grid networks, resulting in significant enhancements in energy efficiency and cost reduction.

2. Energy Forecasting with Machine Learning:

Developed predictive models employing time series analysis and machine learning algorithms to forecast energy consumption patterns, facilitating efficient resource allocation in energy management systems.

3. Anomaly Detection in Power Systems:

Created an anomaly detection system utilizing machine learning techniques to identify and mitigate faults or anomalies in power systems, ensuring grid stability and resilience.

Publications and Research Contributions:

Co-authored multiple papers published in leading conferences and journals, focusing on the convergence of AI, smart grid technologies, and energy management.

Let's connect and explore the fascinating realm of AI-driven solutions in smart grids and energy management!

Arshid Ali's Projects

arshidali84

Config files for my GitHub profile.

heart-disease-prediction-using-machine-learning

Heart Disease dataset, donated in 1988, contains 303 instances with 13 features for classifying heart disease presence (0-4). It's a multivariate dataset from the field of life science, with attributes including age, sex, chest pain type, and more. The dataset is available under a CC BY 4.0 license.

kmeans-clustering-for-online-facebook-sale

Unveiling_the_Power_of_K_Means_Clustering_in_Python_Revolutionizing_Facebook_Live_Selling_in_Thailand_&_ML!

wine-quality-prediction-using-machine-learning

This dataset enables wine quality prediction and binary classification. It comprises attributes related to red and white "Vinho Verde" wines in Portugal. Features include acidity, residual sugar, density, pH, and more. Use it to build ML models, conduct EDA, and assess wine quality. Acknowledgments to the original "Vinho Verde" dataset.

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