THE ML ENGINEER · YEAR ARCHIVE

Newsletter issues from 2020

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#106Dec 2020We wish happy holidays to all our MLE Newsletter subscribers!!, Top 10 Python Libraries of 2020, 2020 Curated List of AI Research, NumPy Deep Dive Illustrated, Metadata Journey at PayPal, Interactive C++ for Data Science + more 🚀ml-research · data-engineering #105Dec 2020Navigating Resposible AI, The NLP Pytorch Tutorial, Research at Microsoft in 2020, Gentle Intro to Concept Drift, Uber on Data Workflows at Scale + more 🚀ai-ethics · nlp · data-engineering #104Dec 2020End-to-end Production ML Monitoring, Metadata Architectures Explained, Applied ML in Production, State of AI Ethics Panel, FOSDEM 2021 CFP HPC & ML + more 🚀mlops · ai-ethics · ai-policy #103Dec 2020UK Data Strategy Consultation, Applying the MLOps Lifecycle, Break into NLP with Andrew NG, Uber on Scale Data Queries, NLP Applications Podcast + more 🚀ai-policy · mlops · nlp #102Nov 2020AI Diversity of Dev & Apps, High Performance NLP, Facebook on Data Discovery, Netflix on Real Time Batch, ML Street Talk Podcast + more 🚀nlp · data-engineering #101Nov 2020E2E Production ML Monitoring, Feature Stores Demystified, ML in Compiler Optimization, Explainable AI in Drug Discovery, Challenges in Deploying ML + more 🚀mlops · explainability #100Nov 2020Cross-vendor GPU Python ML, ML Metadata Management Tools, Practical Guide To Responsible AI, Navigating ML Deployment, Stanford MLSys Seminars + more 🚀mlops · ai-ethics · gpu-compute #99Nov 2020Definitive AI Monitoring Guide, Computational Limits of DL, Safely Rolling out ML to Prod, Audio ML Infrastructure at Spotify, Stop using k8s for ML (use k8s) + more 🚀mlops #98Nov 2020Andrew Ng on Production AI, Netflix's Distributed Tracing Infra, Importance of Data in MLOps, Image Outlier Detection in ML, The State of AI Ethics Report + more 🚀mlops · ai-ethics #97Oct 2020Accelerating GPU Workloads, Software Eng for Deep Learning, The Rise of MLOps, 200 Best ML & Python Tutorials, Running 1M+ Batch Jobs in K8s + more 🚀gpu-compute · mlops · ml-education #96Oct 2020Android Apps with ML on GPU, The Canonical ML Stack, Modern Data Infra Architectures, FB Eng Lead discusses Fairness, AI Ethics - Whose Ethics? Event + more 🚀mlops · ai-ethics #95Oct 2020Real Time ML at Scale, Awful AI Listing Scary Usecases, Scientific Computing with Python, Deep Learning Models Repo, AI for Software Development + more 🚀mlops · ai-ethics · ml-education #94Oct 2020Distributed Training of ML Models, State of AI Report 2020, Embracing Logging in ML, A Brief History of ML Platforms, Whose Ethics? Eastern + Western + more 🚀mlops · gpu-compute · ai-ethics #93Sept 2020GPU Accelerated ML in GameDev, Modular vs E2E ML Platforms, Dagster Data Orchestration, ML for MedTech Monitoring, Whose Ethics? Eastern + Western + more 🚀mlops · gpu-compute · ai-ethics #92Sept 2020Data Version Control with Dmitry, Differential Privacy Series, Which GPUs for Deep Learning, Reinforcement Learning Pathmind, Explainable AI Monitoring + more 🚀mlops · privacy · reinforcement-learning #91Sept 2020Machine learning in cross-vendor & mobile GPUs made simple, AI, Data & Ethics Research, Detecting Shifts in Policy with ML, AI Enabled Code Compilers, AI O'Reilly 2020 Trends to Watch + more 🚀gpu-compute · ai-ethics · nlp #90Sept 2020AI, Data & Ethics Research, AI Summarize Human Feedback, LipSync DeepFake AI Improved, Getting started with ML resource, AI Monitoring & Assurance + more 🚀ai-ethics · reinforcement-learning #89Aug 2020FastAI Practical Data Ethics, Building Conversational AI Apps, Computational Learning Intro, Topic Modelling with Gensim, Optical Character Recog for All + more 🚀ai-ethics · nlp #88Aug 2020FastAI New Course, Libs & Book, Massive Scaling Google Meets, DeepFakes Threat Report, AI Developer Tools Landscape, Beginner to Prof. Dev with Python + more 🚀mlops #87Aug 2020Prod Model Server Features, Computational Causal Inference, Practical AI's 100th Episode, Realistic Tennis AI w Vid2Player, New Jupyter Book Launch + more 🚀mlops · ml-research #86Aug 2020Innovation, Regulation and AI, The Role of AI Product Managers, Data Observability in Production, Graph Algorithms in Industry, Open RL Benchmark 0.3.0 + more 🚀ai-policy · reinforcement-learning #85Aug 2020Experts Recommend ML Books, Why NLP Beyond English, Kubeflow ML Prod Workflow, Configuring Cross-Validation, Philosophers on GPT-3 (feat. AI) + more 🚀nlp · mlops · ml-education #84Jul 2020Netflix On Cutting Data Costs, Awesome Github GPT-3 List, Lessons from ML Prod Monitoring, Airflow Summit Videos are Out, Uber on Editing Massive GeoData + more 🚀mlops · data-engineering · llms #83Jul 2020Building an Enterprise DL Stack, 5 Key Features for ML Platforms, AI Dungeon Open World w GPT3, The State of Apache Airflow, D2IQ KUDO for Kubeflow + more 🚀mlops · llms #82Jul 2020Full Stack Deep Learning Course, Software Engineers in ML, Web Services vs Streaming in ML, Continuous ML (CML) CI/CD, Papers With Code Methods + more 🚀mlops #81Jul 2020Getting ML into Production, Top Books on ML Feature Eng, MSFT Adversarial ML in Industry, Google on Neural Nets for Tables, Getting into a Causal Flow + more 🚀ml-security · nlp · ml-research #80Jun 2020MLflow Joins Linux Foundation, DVC 1.0 features for MLOps, Designing Industrial Scale ML, Machine Learning Operations + more 🚀explainability · mlops #79Jun 2020Model Serving Ecosystem, GitHub Actions for MLOps, Building OSS Tools for NLP Devs, Reinforcement Learning Apps, NLP Transfer Learning at Scale + more 🚀mlops · nlp · reinforcement-learning #78Jun 2020Outlier & Anomaly Detection ML, The State of ML in Python 2020, Applied Homomorphic Encryption, OpenAI NLP API Beta Launch, Continuous Delivery Podcast + more 🚀forecasting · privacy · nlp #77Jun 2020Made with ML Platform, Identifying & Mitigating AI Risks, ACM ByteCast with Donald Knuth, Microsoft NLP Bias Research, Feature Selection with Cont. Data + more 🚀ai-policy · ai-ethics #76May 2020Highlights on EuroPython & ACM, ML in Prod Deployment Guide, Frameworks used by ML Startups, GPT-3 Deep Dive Explanation, Scaling Data with Outliers for ML + more 🚀mlops · llms #75May 2020Microsoft Programming AI, ML Infra for Model Building, Discourse Rethinking Public Data, Advanced NLP Video Course, What to Do When AI Fails + more 🚀nlp · mlops · ai-ethics #74May 2020Coding Habits for Data Scientists, Enterprise AI Adoption 2020, Natural Language Processing 101, AI Scalability & Performance, MLOps is Not Enough + more 🚀mlops · nlp #73May 2020Real Time ML Stream Processing, Statement on Contact Tracing, ICLR 2020 Videos Released, Why TinyML will be Huge, PapersWithCode: A home for ML + more 🚀data-engineering · ai-policy · ml-research #72May 2020Monitoring ML Models in Prod, 65 Free Springer ML Books, Neural Network Music Generator, Open Source Deep Learning, AI, COVID19 & Contact Tracing + more 🚀ai-ethics #71Apr 2020A Practical Intro to Responsible AI, Simulating Real World in Python, Advanced NLP with SpaCy, 500 Free CompSci Courses, Modelling & Simulating Epidemics + more 🚀ai-ethics · nlp · ml-education #70Apr 2020Privacy Preserving AI Lecture, Backpropagation 101 from Thinc, Harvard Offering Free Courses, GPT2 AI Dungeon Game Update + more 🚀privacy · ml-education · nlp #69Apr 2020Insights for Remote ML Teams, Human-in-the-loop in Prod ML, Netflix & Druid for Real Time Data, The Importance of Data Prep + more 🚀mlops · data-engineering #68Apr 2020GitLab Data Lessons Learned, Data Discovery at Spotify, Exploratory Data Analysis Dive, Tokenisers & How Machines Read, Intel Demystifying the AI Stack + more 🚀data-engineering · nlp · mlops #67Mar 2020COVID-19 AI solutions at scale, Democratising Deep Fakes 😬, Shopify on Scaling AI, Industry Reinforcement Learning, Transfer Learning in NLP + more 🚀reinforcement-learning · nlp #66Mar 2020PyTorch ML from Scratch, The MLOps References List, Deep Learning & Info Retrieval, Integrating SHAP Explainability, AI meets operations with OReilly + more 🚀ml-research · explainability · mlops #65Mar 2020Explainability, Security & MLOps, Python Machine Learning Books, DevOps in Machine Learning, A Tour on E2E ML Platforms, Adversarial ML Reading List + more 🚀mlops · explainability · ml-security #64Mar 2020Kubernetes ML for Everyone, Production-Ready ML Systems, Explaining Long Term ML Impact, Quantifying Reproducibility of ML, Adversarial Examples Resource + more 🚀mlops · ai-ethics · ml-security #63Mar 2020Building Blocks of Interpretability, Ethics in AI and Big Data Course, Reviewing Emotional Expressions, Model Explainability for Business, Microsoft's Data Science Process + more 🚀explainability · ai-ethics #62Feb 2020Jurgen's Retrospective AI 2010s, Hyperconnected Missinformation, MLOps: The End of End-to-End, How to Interpret an ML Model, Empirical Quality Metrics for DL + more 🚀ai-ethics · mlops · explainability #61Feb 2020Microsoft's NLP Recipes, Messaging & Data Ingestion++, Why Imbalanced ML is so hard, AI for Data Cleaning at Scale, Training Models with 1b+ Params + more 🚀nlp #60Feb 2020Hands on MLOps for AI at Scale, Why ML Degrades in Production, Kaggle Kernel on Interpretability, Building Domain Specific NLP, Bayesian Product Raking Wayfair + more 🚀mlops · explainability · nlp #59Feb 2020Table Detection & NLP with DL, Towards general conv. agent, State of privacy preserving ML, Distributed Delayed Job Queueing, Applying confidence models + more 🚀privacy · data-engineering #58Jan 2020Feature Stores for ML, Key AI & Data Trends for 2020, LF AI 2019 Year in Review, From local to global XAI, Sampling methods for imbalances + more 🚀mlops · explainability #57Jan 2020Google Research 2019 + Beyond, Facebook OSS Year in Review, AI Lessons Learned with Rakuten, Move fast and break things w AI, Intro to Ethics in AI + more 🚀ai-ethics · ai-policy #56Jan 2020Evolution of ML Infrastructure, 30 Woman Advancing AI, Calculating the Value of Data, Intro to Ethics in AI, A Guide to File Formats in ML + more 🚀mlops · ai-ethics #55Jan 2020Machine Learning System Design, Machine Learning Interviews, A Deep Dive into Online Learning, Unsupervised NLU via GPT-2, Open Source Business Models + more 🚀ml-education · nlp