huangjie-nn

cracking-the-data-science-interview

A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep

deploying-machine-learning-models

Example Repo for the Udemy Course "Deployment of Machine Learning Models"

FedProx

Federated Optimization in Heterogeneous Networks (MLSys '20)

finetune-transformer-lm

Code and model for the paper "Improving Language Understanding by Generative Pre-Training"

FL_synthetic_dataset_generator

Synthetic dataset generator for federated learning.

hello-retail-baseline

kaggle-pku-autonomous-driving

Part of 5th place solution for Peking University/Baidu - Autonomous Driving on Kaggle (https://www.kaggle.com/c/pku-autonomous-driving).

maginification

MLFlow-Demo

sciencebowl2019

huangjie-nn/FL_synthetic_dataset_generator

Synthetic dataset generator for federated learning.

huangjie-nn/cracking-the-data-science-interview

A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep

huangjie-nn/deploying-machine-learning-models

Example Repo for the Udemy Course "Deployment of Machine Learning Models"

huangjie-nn/FedProx

Federated Optimization in Heterogeneous Networks (MLSys '20)

huangjie-nn/finetune-transformer-lm

Code and model for the paper "Improving Language Understanding by Generative Pre-Training"

huangjie-nn/hello-retail-baseline

huangjie-nn/kaggle-pku-autonomous-driving

Part of 5th place solution for Peking University/Baidu - Autonomous Driving on Kaggle (https://www.kaggle.com/c/pku-autonomous-driving).

huangjie-nn/maginification

huangjie-nn/MLFlow-Demo

huangjie-nn/sciencebowl2019

huangjie-nn/stanford-cs-221-artificial-intelligence

VIP cheatsheets for Stanford's CS 221 Artificial Intelligence

huangjie-nn/stanford-cs-229-machine-learning

VIP cheatsheets for Stanford's CS 229 Machine Learning

huangjie-nn/stanford-cs-230-deep-learning

VIP cheatsheets for Stanford's CS 230 Deep Learning

huangjie-nn/transformer-abstractive-summarization

Code for the paper "Efficient Adaption of Pretrained Transformers for Abstractive Summarization"