awesome-machine-learning-engineering
A curated list of articles, papers and tools for managing the building and deploying of machine learning models, aka machine learning engineering.
https://github.com/d18s/awesome-machine-learning-engineering
Last synced: 2 days ago
JSON representation
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Example pipelines
- Learning a Personalized Homepage
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Ad Click Prediction: a View from the Trenches
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Learning a Personalized Homepage
- Distributed Time Travel for Feature Generation
- Distributed Time Travel for Feature Generation
- Ad Click Prediction: a View from the Trenches
- Learning a Personalized Homepage
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Data
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Conference tracks and workshops
- Reliable Machine Learning in the Wild NIPS 2016 workshop
- Reliable Machine Learning in the Wild ICML 2017 workshop
- ECMLPKDD 2016 Industrial track
- Reliable Machine Learning in the Wild NIPS 2016 workshop
- Reliable Machine Learning in the Wild ICML 2017 workshop
- ECMLPKDD 2016 Industrial track
- Reliable Machine Learning in the Wild ICML 2017 workshop
- Reliable Machine Learning in the Wild NIPS 2016 workshop
- Reliable Machine Learning in the Wild ICML 2017 workshop
- KDD 2017 Applied Data Science
- KDD 2018 Applied Data Science
- ECMLPKDD 2016 Industrial track
- ECMLPKDD 2017 Applied Data Science track
- WWW 2018 Industry track
- Reliable Machine Learning in the Wild NIPS 2016 workshop
- ECMLPKDD 2017 Applied Data Science track
- Reliable Machine Learning in the Wild NIPS 2016 workshop
- Reliable Machine Learning in the Wild ICML 2017 workshop
- ECMLPKDD 2016 Industrial track
- ECMLPKDD 2018
- WWW 2018 Industry track
- Reliable Machine Learning in the Wild NIPS 2016 workshop
- Reliable Machine Learning in the Wild ICML 2017 workshop
- ECMLPKDD 2016 Industrial track
- Reliable Machine Learning in the Wild NIPS 2016 workshop
- Reliable Machine Learning in the Wild ICML 2017 workshop
- KDD 2017 Applied Data Science
- KDD 2018 Applied Data Science
- ECMLPKDD 2016 Industrial track
- Reliable Machine Learning in the Wild NIPS 2016 workshop
- Reliable Machine Learning in the Wild ICML 2017 workshop
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Big data on a single machine / on the command line
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Software
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AWS
- Sagemaker
- Simple Workflow
- Data Pipeline
- Batch
- Simple Workflow
- Glue
- Machine Learning - based service that makes it easy for developers of all skill levels to use machine learning technology"
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Managing building models
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Serialising and transpiling models
- sklearn2pmml - Learn pipelines to PMML
- sklearn-porter - learn estimators to C, Java, JavaScript and others
- jpmml-sklearn - line application for converting Scikit-Learn pipelines to PMML
- Predictive Model Markup Language
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Managing building and deploying models
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Deploying models
- Serving - performance serving system for machine learning models (Google)
- deepdetect
- clipper - latency prediction-serving system (Berkeley)
- MLeap
- mxnet-model-server
- hydro-serving - Machine Learning Serving cluster (hydrosphere.io)
- openscoring - time scoring (<1 ms) of R, Scikit-Learn and Apache Spark models (openscoring)
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Google Cloud
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Monitoring models
- Knowledge Repo - generation curated knowledge sharing platform for data scientists and other technical professions.
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Best practice
- Production Data Science
- What’s your ML test score? A rubric for ML production systems
- Introducing the Facebook Field Guide to Machine Learning video series
- Patterns for Research in Machine Learning
- Making Netflix Machine Learning Algorithms Reliable
- Rules of Machine Learning: Best Practices for ML Engineering
- What’s your ML test score? A rubric for ML production systems
- Machine Learning: The High Interest Credit Card of Technical Debt
- Introducing the Facebook Field Guide to Machine Learning video series
- Patterns for Research in Machine Learning
- Production Data Science
- Making Netflix Machine Learning Algorithms Reliable
- Scaling Knowledge at Airbnb
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Related awesome lists
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Where to start
Programming Languages
Categories
Sub Categories
Keywords
machine-learning
6
scikit-learn
5
data-science
4
python
4
tensorflow
4
deep-learning
3
scheduling
2
spark
2
ml
2
workflow
2
serving
2
xgboost
2
realtime
1
scoring
1
serverless
1
caffe
1
gpu
1
image-classification
1
image-search
1
image-segmentation
1
ncnn
1
neural-nets
1
object-detection
1
pytorch
1
pipelines
1
models
1
scipy
1
pydata
1
pandas
1
numpy
1
dask
1
neural-network
1
deep-neural-networks
1
cpp
1
orchestration-framework
1
luigi
1
hadoop
1
workflow-engine
1
sklearn
1
data-pipelines
1
scala
1
transformers
1
apache-spark
1
api
1
lightgbm
1
pmml
1
r
1
real-time
1
collaborative
1
production
1