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Seong-Jin Kim's Projects

awesome-courses icon awesome-courses

:books: List of awesome university courses for learning Computer Science!

click-tools icon click-tools

Command-Line utilities for Click (extracted from Clint).

collmetric icon collmetric

A Tensorflow implementation of Collaborative Metric Learning (CML)

crf icon crf

A pure-Python implementation of the Linear-Chain Conditional Random Fields

ddia-references icon ddia-references

Literature references for “Designing Data-Intensive Applications”

handson-ml icon handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

kaggle_pbr icon kaggle_pbr

My best submission to the Kaggle competition "Predicting a Biological Response", ranked 17th over 711 teams.

lightgbm icon lightgbm

A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.

ml-from-scratch icon ml-from-scratch

Machine Learning From Scratch. Bare bones Python implementations of Machine Learning models and algorithms with a focus on transparency and accessibility. Aims to cover everything from Data Mining to Deep Learning.

n2 icon n2

TOROS N2 - lightweight approximate Nearest Neighbor library which runs faster even with large datasets

nmslib icon nmslib

Non-Metric Space Library (NMSLIB): A similarity search library and a toolkit for evaluation of k-NN methods for generic non-metric spaces.

numerical-linear-algebra icon numerical-linear-algebra

This course contains the notebooks for the Numerical Linear Algebra elective in USF's MSAN program, summer 2017

papers icon papers

Summaries of machine learning papers

prml icon prml

PRML algorithms implemented in Python

pygbm icon pygbm

Experimental Gradient Boosting Machines in Python.

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