HackMD
ML Platform Research Note
Paper
- Clipper: A Low-Latency Online Prediction Serving System
- TensorFlow-Serving: Flexible, High-Performance ML Serving
- A Case for Serverless Machine Learning
- TICTAC: ACCELERATING DISTRIBUTED DEEP LEARNING WITH COMMUNICATION SCHEDULING
- PipeMare: Asynchronous Pipeline Parallel DNN Training
- TFX: A TensorFlow-Based Production-Scale Machine Learning Platform
- Kubebench: A Benchmarking Platform for ML Workloads
- Hidden Technical Debt in Machine Learning Systems
- Deep CTR Prediction in Display Advertising
- Large-Scale Machine Learning at Twitter
- Practical Lessons from Predicting Clicks on Ads at Facebook
- On Challenges in Machine Learning Model Management
- An Experimentation and Analytics Framework for Large-Scale AI Operations Platforms
PPT
- ACCELERATED COMPUTING FOR AI
- PipeDream: Generalized Pipeline Parallelism for DNN Training
- MLOp Lifecycle Scheme for Vision-based Inspection Process in Manufacturing
- [Lecture] SOFA Quick Start
- Bighead: Airbnb’s End-to-End Machine Learning Infrastructure
- Apache Hadoop 机器学习引擎 Submarine 及生态 刘勋
- Scaling Deep Learning on Hadoop at LinkedIn
- MLeap: Productionize Data Science Workflows Using Spark
- Bighead airbnb’s End-to-End Machine Learning Infrastructure
- Machine Learning as Code and Kubernetes with Kubeflow
- Kubebench:Benchmarking ML Workloads on Kubernetes
- ML Ops and Kubeflow Pipelines
- Building AI Platfrom Based on Kubernetes and TensorFlow
- Apache Spark Model Deployment
- What are the Unique Challenges and Opportunities in Systems for ML
- Kubeflow++ Building an Open Source Data Science Platform
- Zipline—Airbnb’s Declarative Feature Engineering Framework
github
- https://github.com/kanonjz/paper
- https://github.com/cortexlabs/cortex
- https://github.com/ucbrise/clipper
- https://github.com/tensorflow/serving
- https://github.com/Angel-ML/serving
- https://github.com/tensorflow/tensorrt
- https://github.com/tensorflow/tfx
- https://github.com/kubeflow/examples
- https://github.com/microsoft/nni
- https://github.com/apache/submarine
- https://github.com/tensorflow/cloud
- https://github.com/Netflix/metaflow
- https://github.com/quantumblacklabs/kedro
- https://github.com/HDI-Project/AutoBazaar
- https://github.com/awslabs/djl
- https://github.com/bentoml/BentoML
Conference
List of Machine Learning and Deep Learning conferences in 2020
https://tryolabs.com/blog/machine-learning-deep-learning-conferences/
- Systems for ML 2018
- SysML Conference 2019
- aiconference
- SOSP 2019 Program
- OpML '19 Conference Program
- ScaledML 2019
- Workshop on AI Systems at SOSP 2019
Talk
- Bighead: Airbnb’s End-to-End Machine Learning Platform-1
- Bighead: Airbnb’s End-to-End Machine Learning Platform-2
- Zipline: Airbnb’s Machine Learning Data Management Platform
- Machine Learning with TensorFlow and PyTorch on Apache Hadoop using Cloud Dataproc (Cloud Next '19)
- Benchmarking Machine Learning Workloads on Kubeflow - Xinyuan Huang, Cisco Systems, Inc. & Ce Gao
- Hadoop {Submarine} Project: Running deep learning workloads on YARN, Wangda Tan, Hortonworks
- SFBigAnalytics_20200825: Apache Submarine: State of the union
- TensorFlow On Spark: Scalable TensorFlow Learning on Spark Clusters
- Simplifying Model Management with MLflow - Matei Zaharia (Databricks) Corey Zumar (Databricks)
- Platform for Complete Machine Learning Lifecycle (mlflow)
- Building and Managing a Centralized Kubeflow Platform at Spotify - Keshi Dai & Ryan Clough, Spotify
- Human-Centric Machine Learning Infrastructure @Netflix
Blog
- Meet Michelangelo: Uber’s Machine Learning Platform
- Twitter meets TensorFlow
- Using Deep Learning at Scale in Twitter’s Timelines
- Introducing FBLearner Flow: Facebook’s AI backbone
- A Tour of End-to-End Machine Learning Platforms
- 3 Common Technical Debts in Machine Learning and How to Avoid Them
- Implementing Apache Submarine — a unified AI Platform
