Popular GitHub Repositories for Learner

The code for our paper "NSP-BERT: A Prompt-based Zero-Shot Learner Through an Original Pre-training Task —— Next Sentence Prediction"

GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner in WWW'23

Implementation of "A Simple Neural Attentive Meta-Learner" (SNAIL, https://arxiv.org/pdf/1707.03141.pdf) in PyTorch

Regular practice on Data Science, Machien Learning, Deep Learning, Solving ML Project problem, Analytical Issue. Regular boost up my knowledge. The goal is to help learner with learning resource on Data Science filed.

Meta learning with BERT as a learner

[NeurIPS 2023 Main Track] This is the repository for the paper titled "Don’t Stop Pretraining? Make Prompt-based Fine-tuning Powerful Learner"

Agent4Edu: Generating Learner Response Data by LLM-based Agents for Intelligent Education Systems (AAAI 2025)

Important Note fastrl version 2 is being developed at fastrl. Note the link in the readme

This is the official repo for Contrastive Vision-Language Alignment Makes Efficient Instruction Learner.

Implementation of the deep learning model with inference pipeline described in the paper "ConTextTab: A Semantics-Aware Tabular In-Context Learner".

Code of paper: "ELECTRA is a Zero-shot learner, Too" -- Prompt-based ELECTRA for zero-shot learning.

Essay Grammar Checker trained on REALEC Corpus using SpaCy

CourseTA is your AI-powered teaching assistant that transforms video lectures into quizzes and summaries helping course creators accelerate content creation and boost learner engagement.

Learner-Verifier Framework for formal synthesis of Control Barrier Functions (CBF).

[Partial] RADLER: (adversarially) Robust Adversarial Distributional LEaRner

Developing a feedback theory-informed natural language processing (NLP) model to enable large-scale evaluation of written feedback, and analysing a large set of feedback extracted from Moodle using this model to understand the presence of student-centred feedback elements, the commonality and differences in feedback provision across disciplines.

we Trying to predict credit card transaction if it's fraud or not, using AWS sagemaker, linear learner. the project was created throw AWS training with the help of a machine learning specialist from AWS

Uplift modelling using meta learners