Taekmin Kim (tantara)

tantara

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Company:@bytedance

Location:Palo Alto, CA

Home Page:linkedin.com/in/taekminkim

Twitter:@taekminkim

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Organizations
SNUCMA
wafflestudio

Taekmin Kim's repositories

JejuNet

Real-Time Video Segmentation on Mobile Devices with DeepLab V3+, MobileNet V2. Worked on the project in 🏝 Jeju island

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PeerNets-pytorch

A pytorch implementation of 'PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks'

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kakao-arena-product-classification

Ranked πŸ₯ˆ2nd(team: baseIine) over 450 teams and won πŸ’°$4,000 in E-commerce Product Classification | Kakao AI Challenge 2018

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tf_examples

TensorFlow examples

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naver-ai-hackathon-2018

Ranked 5th over 200 teams in Naver AI Hackathon 2018

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caffe2-models

A repository for storing pre-trained Caffe2 models.

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Deep-Feature-Flow

Deep Feature Flow for Video Recognition

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Deep-Feature-Flow-Segmentation

Deep Feature Flow for Video Semantic Segmentation

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docs

TensorFlow documentation

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EdgeNets

This repository contains the source code of our work on designing efficient CNNs for computer vision

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faster-rcnn.pytorch

A faster pytorch implementation of faster r-cnn

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Flow-Guided-Feature-Aggregation

Flow-Guided Feature Aggregation for Video Object Detection

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Machine-Learning-for-Algorithmic-Trading-Second-Edition

Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.

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models-1

Models and examples built with TensorFlow

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raspberry-pi-os

Learning operating system development using Linux kernel and Raspberry Pi

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react-caffe2

Caffe2 library for React Native

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rust-lang-book-ko

The Rust Programming Language

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rust-raspberrypi-OS-tutorials

:books: Learn to write an embedded OS in Rust :crab:

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Sentimental-Analysis-for-Hackerearth

Sentimental analysis for Hackerearth Challenge (Predict the Happiness)

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shopping-classification

μ‡Όν•‘λͺ° μƒν’ˆ μΉ΄ν…Œκ³ λ¦¬ λΆ„λ₯˜ λŒ€νšŒμ˜ baseline

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SNU-nlp-demo

Demo for sentiment analysis with FastText, NLP(2017 Fall) at SNU

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tensorflow

Computation using data flow graphs for scalable machine learning

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tpu

Reference models and tools for Cloud TPUs.

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