Popular GitHub Repositories for Publications

links to conference publications in graph-based deep learning

A curated list of awesome imitation learning resources and publications

Links to conference/journal publications in automated fact-checking (resources for the TACL22/EMNLP23 paper).

Distributed Machine Learning Patterns from Manning Publications by Yuan Tang https://bit.ly/2RKv8Zo

Code for Machine Learning with TensorFlow: 2nd Edition Published by Manning Publications

Learn Generative AI with PyTorch (Manning Publications, 2024)

Semantic search engine indexing 110 million academic publications

STriP Net: Semantic Similarity of Scientific Papers (S3P) Network

Python Streamlit web app utilizing OpenAI (GPT4) and LangChain LLM tools with access to Wikipedia, DuckDuckgo Search, and a ChromaDB with previous research embeddings. Ultimately delivering a research report for a user-specified input, including an introduction, quantitative facts, as well as relevant publications, books, and youtube links.

A curated list of graph reinforcement learning papers.

Generate custom detailed survey paper with topic clustered sections and proper citations, from just a single query in just under 30 mins !!

Resources (conference/journal publications, references to dataset) for harmful memes detection.

End-to-end NLP tool to analyze research publications. Published in Ecology & Evolution 2021.

Automatic knowledge graph generation for Obsidian.md

Reference code base for ML Engineering in Action, Manning Publications Author: Ben Wilson

This repository contains list of publications on the application of Graph Neural Network in Wireless Communication

Powerful document clustering models are essential as they can efficiently process large sets of documents. These models can be helpful in many fields, including general research. Searching through large corpora of publications can be a slow and tedious task; such models can significantly reduce this time.

Repository for the companion Colab notebook of the Domain-Specific Small Language Models book.

The code for How Machine Learning Works, Manning Publications

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