Shixin's starred repositories
neural_collaborative_filtering
Neural Collaborative Filtering
styleguide
Style guides for Google-originated open-source projects
Reco-papers
Classic papers and resources on recommendation
tensorflow-without-a-phd
A crash course in six episodes for software developers who want to become machine learning practitioners.
TensorFlow-Course
:satellite: Simple and ready-to-use tutorials for TensorFlow
Semantic-Segmentation-Suite
Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!
data-validation
Library for exploring and validating machine learning data
tf-estimator-tutorials
This repository includes tutorials on how to use the TensorFlow estimator APIs to perform various ML tasks, in a systematic and standardised way
pure-bash-bible
đź“– A collection of pure bash alternatives to external processes.
tensorflow-recommendation-wals
An end-to-end solution for website article recommendations based on Google Analytics data. Uses WALS matrix-factorization in TensorFlow, trained on Cloud ML Engine. Recommendations served with App Engine Flex and Cloud Endpoints. Orchestration is performed using Airflow on Cloud Composer. See the solution tutorials at:
cloudml-samples
Cloud ML Engine repo. Please visit the new Vertex AI samples repo at https://github.com/GoogleCloudPlatform/vertex-ai-samples
data-science-on-gcp
Source code accompanying book: Data Science on the Google Cloud Platform, Valliappa Lakshmanan, O'Reilly 2017
training-data-analyst
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
system-design-primer
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
cs231n.github.io
Public facing notes page
TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
stanford-tensorflow-tutorials
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
DeepNLP-models-Pytorch
Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)
state-of-the-art-result-for-machine-learning-problems
This repository provides state of the art (SoTA) results for all machine learning problems. We do our best to keep this repository up to date. If you do find a problem's SoTA result is out of date or missing, please raise this as an issue or submit Google form (with this information: research paper name, dataset, metric, source code and year). We will fix it immediately.
sklearn-pandas
Pandas integration with sklearn
PyTorchZeroToAll
Simple PyTorch Tutorials Zero to ALL!
Netflix-Prize
The code I used to get in the top #150 in the Netflix Prize