prrao87/pydantic-benchmarks

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Created over 1 year ago
Updated 8 months ago

prrao87/pydantic-benchmarks

prrao87

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Benchmarks testing the performance of various releases of Pydantic v2 🦀

fine-grained-sentiment

A comparison and discussion of different NLP methods for 5-class sentiment classification on the SST-5 dataset.

tweet-stance-prediction

Applying NLP transfer learning techniques to predict Tweet stance toward a topic

Jupyter Notebook

db-hub-fastapi

Async bulk data ingestion and querying in various document, graph and vector databases via their Python clients

kuzudb-study

Benchmark study on KùzuDB, an embedded OLAP graph database, on an artificial social network dataset

duckdb-study

Compare DuckDB, Polars and Pandas for generating an artificial dataset of persons and companies

lancedb-study

Benchmark study on LanceDB, an embedded vector DB, for full-text search and vector search

neo4j-python-fastapi

Bulk ingest data into Neo4j using sync or async Python, and expose the data via FastAPI

fine-grained-sentiment-app

A Flask LIME explainer app for fine-grained sentiment classification.

blog

Posts related to Data Science, engineering and machine learning.

Jupyter Notebook

topic-modelling

Comparing the scalability and quality of topic models in Gensim and PySpark

patent-classification

Classify international patents into one of eight categories based on the text of their titles & abstracts using DistilBert & ONNX Runtime

fine-grained-sentiment-app-streamlit

A LIME explainer app for fine-grained sentiment classification, written using Streamlit.

graphdb-case-studies

Case studies showing the analysis of connected data using different graph databases and their Python client libraries

prrao87.github.io

Archived. My blog is now moved to https://github.com/thedataquarry

rag-data-ops

Code for data ops when building RAG applications using LangChain and LlamaIndex

mteb-validation

Compare different embedding models from MTEB leaderboard

spectral-line-plots

Plot multiple lines with spectral colors to simultaneously compare similar datasets