Popular GitHub Repositories for Aspects

Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automating these high-value generic R&D processes through our open source R&D automation tool RD-Agent, which lets AI drive data-driven AI.

A Full Stack ML (Machine Learning) Roadmap involves learning the necessary skills and technologies to become proficient in all aspects of machine learning, including data collection and preprocessing, model development, deployment, and maintenance.

Always sparse. Never dense. But never say never. A Sparse Training repository for the Adaptive Sparse Connectivity concept and its algorithmic instantiation, i.e. Sparse Evolutionary Training, to boost Deep Learning scalability on various aspects (e.g. memory and computational time efficiency, representation and generalization power).

Hands-on MLOps projects to explore and learn the practical aspects of machine learning engineering for production.

StageMate is the smart assistant for your presentation. It will cover all aspects of your pitch from skipping slides to reminding you if you miss some major point.

IARM: Inter-Aspect Relation Modeling with Memory Networks in Aspect-Based Sentiment Analysis, EMNLP 2018

EMNLP 2020 - Summarizing Text on Any Aspects

Aspect-Based Sentiment Analysis

Controlling Argument Generation via topic, stance, and aspect

Codes, scripts, and notebooks on various aspects of transformer models.

Developed BERT, LSTM, TFIDF, and Word2Vec models to analyze social media data, extracting service aspects and sentiments from a custom dataset. Provided actionable insights to telecom operators for customer satisfaction and competitive analysis.

IJCAI 2022 Long Presentation: An inductive KG link prediction utilizing neighboring relations from two aspects and using the MI maximization.

Welcome to the Machine Learning Projects Repository! This repository hosts a collection of predictive modeling projects, each focusing on different aspects of data analysis and machine learning. These projects cover a wide range of topics, including linear regression, multiple regression

Comprehensive LLMs repo, where I cover both theoretical and practical aspects of LLMs.

This project is built around PyTorch-Lightning, offering a structured and friendly environment for anyone exploring sequential recommendation systems. This platform is designed to simplify the machine learning workflow, letting you focus more on the strategic aspects of model development and less on setup complexities.

An easy to use and understand method for the average user to test various aspects of intelligence of your LLM in only one run.

Machine learning and AI projects require managing diverse data sources, vast data volumes, model and parameter development, and conducting numerous test and evaluation experiments. Overseeing and tracking these aspects of a program can quickly become an overwhelming task.

Implements gans on toy datasets and preliminary ML datasets for showing certain aspects of convergence and stability. Tries to cover various loss functions defined over the years.

Service to examine data processing pipelines (e.g., machine learning or deep learning pipelines) for uncertainty consistency (calibration), fairness, and other safety-relevant aspects.

My assignment submissions for the Fall 2023 Large Language Models course at Sharif University of Technology. The assignments cover topics such as parameter efficient fine-tuning, multi-modal LLMs and evaluating LLMs on various aspects.