Search Results for "basqet-notes"

Super comprehensive deep learning notes is a massive and well-structured collection of deep learning notebooks that serve as a comprehensive study resource for anyone wanting to learn or reinforce concepts in computer vision, natural language processing, deep learning architectures, and even large-model agents. The repository contains hundreds of Jupyter notebooks that are richly annotated and organized by topic, progressing from basic Python and PyTorch fundamentals to advanced neural network designs like ResNet, transformers, and object detection algorithms. ...

LineSolv is a natural-language calculator that understands phrases like $20 in euro - 5% discount or what is the 5 plus pi times five. It combines a powerful Go-based arithmetic engine with a clean, distraction-free desktop UI. Built with Wails v2 (Go + WebView), Vite, TypeScript, and CSS custom properties for theming.

This repository contains lecture notes, slides, assignments, and code for a university-level Natural Language Processing course. It spans core NLP topics such as language modeling, sequence tagging, parsing, semantics, and discourse, alongside modern machine learning methods used to solve them. Students work through programming exercises and problem sets that build intuition for both classical algorithms (like HMMs and CRFs) and neural approaches (like word embeddings and sequence models). ...

This project hosts linguistic annotations and guidelines for clinical text. We plan to include several types of annotation (Token, POS and Parse) in WordFreak format on clinical notes originally from the i2b2/VA NLP challenges. The guidelines are copyrighted, but free for the community to use. Annotation in WordFreak format contains only linguistic labels and character offsets, and can be distributed independently from the note text. Instruction is provided on setting up WordFreak for aligning/visualizing the annotations with the source text, which should be obtained through the official i2b2 data host https://www.i2b2.org/NLP/DataSets/Main.php.