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sandy4321's Projects

wtte-rnn icon wtte-rnn

WTTE-RNN a framework for churn and time to event prediction

wttsf_python icon wttsf_python

Materials of project per the competition of https://www.kaggle.com/c/web-traffic-time-series-forecasting/

wvplots icon wvplots

Pre-packaged plots in R (on top of ggplot2)

ww-trends-2021 icon ww-trends-2021

Repo to accompanying the paper: "Predicting trends in the quality of state-of-the-art neural networks without access to training or testing data"

www.mlcompendium.com icon www.mlcompendium.com

The Machine Learning & Deep Learning Compendium was a list of references in my private & single document, which I curated in order to expand my knowledge, it is now an open knowledge-sharing project compiled using Gitbook.

x-temporal icon x-temporal

A general video understanding codebase from SenseTime X-Lab

xai-bench icon xai-bench

XAI-Bench is a library for benchmarking feature attribution explainability techniques

xarray icon xarray

N-D labeled arrays and datasets in Python

xcsvm icon xcsvm

Extreme Classification SVMs

xfiles-dana icon xfiles-dana

Neural Networks should be Functional Primitives or: a neural network accelerator for RISC-V microprocessors

xformers icon xformers

Hackable and optimized Transformers building blocks, supporting a composable construction.

xgbfi icon xgbfi

XGBoost Feature Interactions & Importance

xgbfir icon xgbfir

XGBoost Feature Interactions Reshaped

xgboost icon xgboost

Large-scale and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, on single node, hadoop yarn and more.

xgboost-from-scratch icon xgboost-from-scratch

This repo contains a few tree based boosting algorithms implemented in python from scratch. This code relates to a medium.com article which I wrote explaining my journey to understanding how XGBoost works under the hood

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