Zahra Taheri
zahta
AI & Machine Learning Expert | Tackling Complex Challenges in Computer Vision, Healthcare AI, GNNs, LLMs & Knowledge Graphs
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Course: Graph Machine Learning focuses on the application of machine learning algorithms on graph-structured data. Some of the key topics that are covered in the course include graph representation learning and graph neural networks, algorithms for the world wide web, reasoning over knowledge graphs, and social network analysis.
In this repository, you can find my solutions to some exercises of the book "Understanding Machine Learning From Theory to Algorithms" by Shai Shalev-Shwartz and Shai Ben-David.
In this repository, I have written about my experiences in studying Machine learning. Also, I have included the solutions of some Machine learning exercises and my educational projects.
The main focus of this project is to visualize the spreading of the Coronavirus and to perform machine learning, time series, and deep learning algorithms on the COVID-19 data to anticipate the future effects of the pandemic. Moreover, we study the impact of some other parameters in predicting COVID-19 spread.
In this repository, I have written some of my experiences in studying deep learning. Also, I have included some good resources and some of my exercises and educational projects. Furthermore, some good references about graph neural networks (GNNs) have been added.
I want to build a neural network from scratch with Python to better understand how neural networks work.
Repositories
10Course: Graph Machine Learning focuses on the application of machine learning algorithms on graph-structured data. Some of the key topics that are covered in the course include graph representation learning and graph neural networks, algorithms for the world wide web, reasoning over knowledge graphs, and social network analysis.
I want to build a neural network from scratch with Python to better understand how neural networks work.
In this repository, you can find my solutions to some exercises of the book "Understanding Machine Learning From Theory to Algorithms" by Shai Shalev-Shwartz and Shai Ben-David.
In this repository, I have written about my experiences in studying Machine learning. Also, I have included the solutions of some Machine learning exercises and my educational projects.
The main focus of this project is to visualize the spreading of the Coronavirus and to perform machine learning, time series, and deep learning algorithms on the COVID-19 data to anticipate the future effects of the pandemic. Moreover, we study the impact of some other parameters in predicting COVID-19 spread.
A curated list of papers and resources based on "Large Language Models on Graphs: A Comprehensive Survey".
In this repository, I have written some of my experiences in studying deep learning. Also, I have included some good resources and some of my exercises and educational projects. Furthermore, some good references about graph neural networks (GNNs) have been added.
Fundamental and Useful Tools and Tips for Data Science
This repository contains codes and data related to the paper "FunQG: Molecular Representation Learning Via Quotient Graphs". A pre-print version of this paper is currently available at
Course: Optimization for Data Science