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THE ML ENGINEER Issue #9     This week in Issue #9: Tools to scale your production machine learning, outlier detection, how facebook scales ML, improving DL with transfer learning, towards federated learning, quantum machine learning, industrial visualisation libraries, ML jobs, conferences and more!   Support the ML Engineer! Forward the email, or share the online version on 🐦 Twitter,  💼 Linkedin and  📕 Facebook!   If you would like to suggest articles, ideas, papers, libraries, jobs, events or provide feedback just hit reply or send us an email to a@ethical.institute!         Tools to scale your production ML Chief Scientist at the Institute for Ethical AI & ML Alejandro Saucedo covers multiple tools available to scale your production machine learning in a short talk at FOSDEM 2019. In this talk, Alejandro covers open source machine learning frameworks in explainability, model & data versioning and orchestration including DVC, Seldon, Pachyderm, CombustML, Algorithmia, SHAP, and more.       Outlier Detection by ML for ML Great post by the Seldon team on anomaly/outlier detection using machine learning for machine learning models. The post provides background on the different types of outlier detection, as well as the typical approaches used to identify them. It goes into detail on 4 implemented algorithms, namely sequence to sequence LSTMs, variational auto-encoders, isolation forests and mahalanobis distance.       How Facebook scales their ML A high level overview that tackles the motivations, challenges and solutions for scaling the machine learning capabilities at Facebook. The talk also references a great talk from Facebook at a machine learning conference where they talk about their ML infrastructure.       Transfer Learning to improve DL Jason from Machine Learning Mastery brings us an excellent tutorial on transfer learning. The article covers the definition of transfer learning, and a hands on example on a multi-class classificaiton problem using a neural network and comparing multiple models     Towards Federated Learning Fascinating paper by Google on Federated Learning - a method that allows for machine learning models to be trained across multiple edge devices in the network instead on a central server. This means that models can be trained from mobile phones or laptops without requiring the data to be transferred to a central server. This is really exciting as it could have very positive impact on data privacy. Gavin Belson would be proud.     Quantum ML Online Course For anyone looking to jump on the quantum hype train, the University of Toronto has launched a course on quantum machine learning. Although there's no blockchain on this course (at least for now), taking on such a nieche intersection it has surely managed to get noticed by the community, certainly with a lot of mixed opinion.       MLOps = Featured OS Libraries We are excited to see the Awesome MLOps list growing to almost 300 stars now! Thanks to everyone for your support! This week's edition is focused on industrial strength visualisation frameworks which fall on our Responsible ML Principle #5. The four featured libraries this week are:   Plotly.py - An interactive, open source, and browser-based graphing library for Python. Pixiedust - PixieDust is a productivity tool for Python or Scala notebooks, which lets a developer encapsulate business logic into something easy for your customers to consume. ggplot2 - An implementation of the grammar of graphics for python. seaborn - Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics.   If you know of any libraries that are not in the "Awesome MLOps" list, please do give us a heads up or feel free to add a pull request!        MLJobs = Jobs & Careers We showcase Machine Learning Engineering jobs (primarily in London for now) to help our community stay up to date with great opportunities that come up. It seems that the demand for data scientists continues to rise!   Junior Opportunities   Seldon is hiring for a Machine Learning / Data Engineer in London Atlas ML is hiring for a Machine Learning / NLP Engineer in London Migacore is hiring for a Machine Learning Engineer in London CloudNC is hiring for a Machine Learning Engineer in London Babylon Health is hiring for a Machine Learning Engineer in London   Mid-level Opportunities QuantumBlack is hiring for a Senior Machine Learning Engineer in London Proportunity is hiring for a Senior Machine Learning Engineer in London Twitter is hiring for a Senior Machine Learning Engineer in London StreetBees is hiring for a Senior Data Scientist in London Apple is hiring for a Senior Machine Learning Engineer in London Expedia is hiring for a Principal Data Scientist in London   Leadership Opportunities Fractal Labs is hiring for a VP of Engineering in London Distributed is hiring for a VP of Engineering in London FactMata is hiring for a Head of Machine Learning in London Skyscanner is hiring for a Senior Director of Sciences in London       MLConf = Conferences & Events We feature conferences that have core  ML tracks (primarily in Europe for now) to help our community stay up to date with great events coming up.   Technical Conferences   PyCon Belarus [15/02/2019] - The 5th edition of the Python conference in Minsk, Belarus. We'll be speaking on Machine Learning Explainability and Bias Evaluation.   Machine Learning Prague [22/02/2019] - A practical conference on machine learning & DL in Prague, CZ.   AI Conference Beijing [18/06/2019] - O'Reilly's signature applied AI conference in Asia in Beijing, China.     Business Conferences   Big Data & AI Tech World [12/03/2019] - AI & Big Data Business conference in London, UK. If you are around, do join our talk on AI Explainability.   AI Expo Global [19/04/2019] - Global conference on artificial intelligence in London, UK. Come join us at our talk on AI orchestration at scale.       © 2018 The Institute for Ethical AI & Machine Learning