Popular GitHub Repositories for Wine Reviews

A helpful 5-page machine learning cheatsheet to assist with exam reviews, interview prep, and anything in-between.

[Nature Reviews Bioengineering?] Application of Large Language Models in Medicine. A curated list of practical guide resources of Medical LLMs (Medical LLMs Tree, Tables, and Papers)

Instant AI code reviews

AI-powered tool for efficient abstract and PDF screening in systematic reviews.

Active learning for systematic reviews

Open source AI code reviews — just like your senior dev would do.

A deliberately vulnerable banking application designed for practicing Security Testing of Web App, APIs, AI integrated App and secure code reviews. Features common vulnerabilities found in real-world applications, making it an ideal platform for security professionals, developers, and enthusiasts to learn pentesting and secure coding practices.

Codai is an AI code assistant that helps developers through a session-based CLI, providing intelligent code suggestions, refactoring, and code reviews based on the full context of the project.

? Give Claude AI superpowers for GitHub workflows. Transform "fix stuff" commits into professional messages, generate intelligent changelogs, and get AI code reviews - all with one command.

Google's Code Review extension for the Gemini CLI that reviews your code changes

A GitHub Action that automatically reviews pull requests using Google's Gemini AI.

Aspect extraction from product reviews - window-CNN+maxpool+CRF, BiLSTM+CRF, MLP+CRF

Simple Pinecone + OpenAI framework to do RAG on movie reviews (or anything else)

Systematic Literature Review (SLR) using AI involves leveraging artificial intelligence techniques to automate and expedite the process of reviewing and synthesizing large volumes of scholarly literature.

Examples on how to use various LLM providers with a Wine Classification problem

A PyTorch CNN for classifying the sentiment of movie reviews, based on the paper "Convolutional Neural Networks for Sentence Classification" by Yoon Kim (2014).

A summarization of Transformer-based architectures for CV tasks, including image classification, object detection, segmentation, and Few-shot Learning. Keep updated frequently.

ACL 2020 Unsupervised Opinion Summarization as Copycat-Review Generation

Successfully developed a machine learning model which can predict whether an online review is fraudulent or not. The main idea used to detect the fake nature of reviews is that the review should be computer generated through unfair means. If the review is created manually, then it is considered legal and original.

Sentiment Analysis for Arabic Text (tweets, reviews, and standard Arabic) using word2vec