moradbeikie Goto Github PK

2023_imageclefmed_gans_submissions

Repo for which users will create pull requests for subissions (ImageCLEGmedical GAN challenge).

awesome-persian

لینک‌های ایرانی توسعه و طراحی

bertopic

Leveraging BERT and c-TF-IDF to create easily interpretable topics.

chain-of-thoughtspapers

A trend starts from "Chain of Thought Prompting Elicits Reasoning in Large Language Models".

decsearch

Decentralized search on power-law graphs

deep-learning

deep-learning-nlp

:satellite: Organized Resources for Deep Learning in Natural Language Processing

deeplearn

Implementation of research papers on Deep Learning+ NLP+ CV in Python using Keras, Tensorflow and Scikit Learn.

hyperparameter-optimization-of-machine-learning-algorithms

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

image-processing

kgtk-notebooks

large-language-models

Large Language Models (LLMs) tutorial

lectures

Oxford Deep NLP 2017 course

meta-learning

meta learning tutorial

multimodal-gpt

Multimodal-GPT

news-recommendation-engine

A real time news recommendation application.

nlp-models-tensorflow

Gathers machine learning and Tensorflow deep learning models for NLP problems

nlp-progress

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

persianstemmer-python

PersianStemmer-Python

personal_recommendation-master

The personalized recommendation system is an intelligent platform based on massive data mining. It can simulate store sales personnel to provide product information and suggestions to customers, and provide fully personalized decision support and information services for customers' shopping. Its goal is to Satisfying the needs of users, meeting the needs that users are not aware of, or realizing, but not expressing the needs, allowing users to go beyond the individual's vision and avoid seeing the trees without seeing the forest. A good recommendation system can greatly increase user loyalty and bring huge benefits to e-commerce. Personalized recommendation is to recommend information and products of interest to users according to their interests and purchasing behavior. As the scale of e-commerce continues to expand, the number and variety of products grow rapidly, and customers need to spend a lot of time to find the products they want to buy. This kind of browsing of a large amount of unrelated information and product processes will undoubtedly cause consumers who are drowning in information overload problems to continue to lose. In order to solve these problems, a personalized recommendation system came into being. The recommendation system is a branch of data mining. It is a special data mining system, which is mainly reflected in the real-time and interactivity of the recommendation system. The system recommends information that meets the interests of the user according to the user's interests, also known as the personalized recommendation system. It not only based on the user's past history, but also needs to react in real time with the behavior of the current period of time, and correct and optimize the recommendation result according to the feedback result of interaction with the user.

project_ir

qlora

QLoRA: Efficient Finetuning of Quantized LLMs

query-expansion

Query Expansion via thesaurus

recommendation-system

recommendation system tutorial

recommenders

Best Practices on Recommendation Systems

recommendersystem-paper

This repository includes some papers that I have read or which I think may be very interesting.

reinforcement-learning

reinforcement-learning-an-introduction

Solutions to exercises in Reinforcement Learning: An Introduction (2nd Edition).

roco-dataset

Radiology Objects in COntext (ROCO): A Multimodal Image Dataset

search-engine-