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matthieuvion's repositories

lmd_ukr

Custom dataset of Le Monde (236 k comments), 1-year-coverage-on-Ukraine & custom made associated API (need Subscriber credentials)

Language:Python4 10

lmd_viz

https://matthieuvion.github.io/lmd_viz/ 236k comments of Le Monde on Ukraine. A proxy to measure people' engagement. Semantic search & SBERT models testing via Sentence-Transformer / Faiss

Language:HTML4 10

Streamlit-based dashboard that collect, aggr. and visualize player's stats from Call of Duty Warzone1. Also deploy our model (cf. /match2kd repo) to predict game difficulty ("lobby kd") from game features.

Language:Python4 10

match2kd

Save thousands of API calls. Custom model & dataset aiming at predicting a game difficulty score ("lobby avg kd") without calling players' games history stats and profiles.

Language:Jupyter Notebook3 10

wzlight

Light asynchronous wrapper for COD Warzone (1) API. Available on PyPi.

Language:Python300

lmd_classi

Classifier(s). Complete guide SetFit vs fine-tuned Mistral-7B vs. quantized ONNX model based on multi-e5 embeddings

Language:Jupyter Notebook200

databricks-xgb

Distributed XGB on Spark with MLFlow model tracking. Code & notes on compatibility of (3!) XGB variants with PySpark/Databricks/MLFlow. Ensure notebook works with Community Edition.

Language:Jupyter Notebook1 10

lstm-gpu-jupyter

LSTM (PyTorch) , time series prediction: a benchmark case w/ and w/o stationarity + scaling

Language:Jupyter Notebook100

mt-leaderboard

Just to crunch some stats. Reverse engineering unofficial/undocumented API for Monster Train (game) daily challenge scoreboards.

Language:C#100

spark-cluster

Steps to deploy a local spark cluster w/ Docker. Bonus: a ready-to-use notebook for model prediction on Pyspark using spark.ml Pipeline() on a well known dataset

Language:Jupyter Notebook1 10

lmd-fastapi-docker

Containerize (Docker) and serve (FastAPI) lmd-comment classifier (ONNX).

Language:Python010

matthieuvion

Curious

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