Notebooks for fine-tuning a BERT model and training a LSTM model for financial QA
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Updated
Apr 13, 2020 - Jupyter Notebook
Notebooks for fine-tuning a BERT model and training a LSTM model for financial QA
A notebook used to perform image classification and clustering of Human Trafficking images.
Jupyter notebooks to help with search relevancy measurements, optimized for Quepid.
A notebook example illustrating Graphyp
Collection of different kernels related to Machine Learning, NLP, Deep Learning, AI and cryptocurrencies..
Some information retrieval algorithms and datastructures (inverted index, ranking (bm25, tf, idf scores), fuzzy search, ...)
compilation of notebooks
Notebooks with source code for self-study experiment with LLM chain and agent for information retrieval on Nebulous: Fleet Command datasets.
A notebook on review classification for movies featured on the imdb page
Cheng-Lin Li's Data Scientist Notebook
📔 [WiP] Writing of the prediction model and plataform for NEURONE.
a notebook and python code aimed at demonstrating information retrieval using binary independence model
A next-generation notebook that uses embeddings for semantic search and 3D visualization of notes.
Hybrid RAG with three retrievers—Lexical (BM25), Semantic (embeddings), and Hybrid (Reciprocal Rank Fusion) — parallel retrieval, Llama 3 generation, and side-by-side evaluation with reproducible notebooks.
Information Retrieval Project: This repository contains a suite of Python tools and a Jupyter notebook for simple data processing, inverted indexing, and boolean querying, complemented by detailed experimental analyses.
This repository contains jypytor notebook for query refinement and uses MAP and TNSE graphs to visualize the query shifting.
An interactive insurance policy query-answering notebook with a Retrieval-Augmented Generation (RAG) pipeline with semantic search, caching, and GPT-based response generation.
A Python-based Jupyter notebook system for high-recall text retrieval in large databases, leveraging active learning to efficiently label instances and train models for identifying relevant documents.
It includes steps such as text pre-processing, document indexing, and query processing using the NLTK library and other NLP tools in the Jupyter Notebook environment. The Cranfield collection was used in the project.
Persian Author Classification: A machine learning project leveraging natural language processing techniques to classify Persian texts by author. The repository contains Jupyter notebooks for both model training and data scraping, a detailed project report, and supplementary source code.
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