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#383Apr 2026LLMs are Databases, Really, NVIDIA Optimization for Agents, Can I Run AI Locally? Yes., Kafka Guide to Distributed Messaging, What 81,000 People Want from AI + more 🚀llms · explainability #297Aug 2024On Being a Senior Engineer, Postgres as a Search Engine, What's Going on in ML, How Google Search Works, Good vs Bad Code Refactoring + more 🚀explainability #270Feb 2024META's V-JEPA vs OpenAI Sora, The MLOps Bookshelf, Google DeepMind Gemini 1.5, Unit Tests using LLMs at Meta, Mistral-7B on an Acid Trip + more 🚀generative-ai · llms · explainability #243Aug 2023Stanford Course on Intro to ML, ML Models Learn vs Generalise, Building Llama from Scratch, MLFlow Tracking and MinIO, MLSecOps Kubeflow Exploration + more 🚀ml-education · explainability · llms #211Jan 2023Check out our new Awesome 2022-2023 Year-In-Review & Tech Predictions List 🚀, 2022-2023 Reviews & Predictions, Algos & Data Structures to Try, Day-1 Decisions Make or Break, Math for Computer Science & ML, Which AI Explanation to Choose + more 🚀explainability · ml-education #173Apr 2022Linkedin's Explainable AI RecSys, Google's AI Autogen Summary, OpenAI's Text to Image Model, Wisdom from 50+ Years of Code, Continuous Intelligence at Scale + more 🚀explainability · generative-ai · mlops #166Feb 2022Data Scientists and Kubernetes, Cross Vendor GPU Acceleration, Open Python ML Inference Server, Building ML Infra at Netflix, Interpretable Machine Learning + more 🚀mlops · gpu-compute · explainability #162Jan 2022MLOps Meetup Online this Week, Architecture Series for MLOps, Testing Approach in Data Science, A Gentle Intro to Shapley Values, Kubernetes the Documentary + more 🚀mlops · explainability #161Jan 2022Principles for Responsible AI, Google Research ML Themes, Introduction to Explainable ML, ML Architectures from Industry, Validation & Testing of ML Models + more 🚀ai-ethics · explainability #152Nov 2021MLOps LDN November Meetup, Scalable Explainable NLP Search, KubeCon North America 2021, AI begins with Data Quality, Reflections 10k hrs Programming + more 🚀mlops · explainability #148Oct 2021Linkedin's Approach to XAI, Prod ML Resources Curated List, Top Places to Work for ML, ML, AI & Data Landscape (MAD), Training System for Industry Scale + more 🚀explainability #140Aug 2021CompSci Favourite Papers, AI & Data Trends to Watch, Language Model Learnings, Trending Open Source MLOps, TorchServe Model Optimization + more 🚀mlops · explainability #139Aug 2021StackOverflow 2021 Dev Survey, Alibi for ML Explainability, Data Science Role Evolution, CPU Transformer Optimization, Open End-to-end MLOps Platform + more 🚀explainability · llms · mlops #133Jul 2021Pitfalls of Causal Inference in XAI, 7 Layers of MLOps Security, Growing Large Language Models, Automated Data Wrangling, Clever vs Insightful Code + more 🚀explainability · mlops · llms #130Jun 2021All-Things-Python at Netflix, Monitoring ML Systems Course, AI Risk and Liability in Industry, Kubernetes Learning from Scratch, What is Your ML Model Hiding + more 🚀mlops · ai-policy · explainability #115Feb 2021Towards Simple Trustworthy AI, Python Developers Survey 2020, SpaCy 3.0 Launch Highlights, Neural Massive Online Multiplayer, Teaching Cars to See at Scale + more 🚀nlp · ai-agents · explainability #107Jan 2021Year Review Papers with Code, Machine Learning going Realtime, An eXplainability toolbox for ML, Simplifying Outlier Detection, Public Engineering Career Ladder + more 🚀explainability · forecasting · ml-research #101Nov 2020E2E Production ML Monitoring, Feature Stores Demystified, ML in Compiler Optimization, Explainable AI in Drug Discovery, Challenges in Deploying ML + more 🚀mlops · explainability #80Jun 2020MLflow Joins Linux Foundation, DVC 1.0 features for MLOps, Designing Industrial Scale ML, Machine Learning Operations + more 🚀explainability · mlops #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 #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 #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 #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 #50Dec 2019Data Science Best Practices, A Contract for the Web, Deep Learning Indaba 2019, Uncertainty Quantification in DL, Google XAI Whitepaper + more 🚀explainability · ml-research · mlops #44Oct 2019Awesome AI Guidelines List, MLFlow simplifying model mgmt, Choosing intuitive visualisations, ML Explainability at AI O'Reilly, Machine learning in 6 steps + more 🚀ai-ethics · explainability #37Sept 2019Real Time NLP: Spacy and Kafka, Becoming an ML practitioner, Cracking the black box (XAI), Notebook innovation at Netflix, How AI solves scale complexities + more 🚀mlops · explainability · ml-education #33Aug 2019Brooklin for data streaming, Tensorflow AI Interpretability, LIDAR and its smart applications, All hail the (AI) algorithm, Machines (and AI) Gone Wrong + more 🚀data-engineering · explainability · ai-ethics #31Jul 2019End-to-end XAI in production, Causal inference to improve UX, Managing ML in enterprise, Intro to Adversarial Examples, The GAN Story so far + more 🚀explainability · ml-research · ml-security #30Jul 2019Production-level ML Explainers, AI Explanations w Counterfactuals, Privacy & Cybersecurity Merging, Hightlights of AI O'Reilly Beijing, 18 Impressive GANs Applications + more 🚀explainability · ml-security · generative-ai #29Jul 2019Major trends in AI & Data, Production-level AI Explanations, 85% of Big Data Projects Fail, ML Mastery on building GANs, Question-answering AI in K8s + more 🚀explainability · data-engineering · ml-security #28Jul 2019The state of AI in 2019, Production ML in 2019, Model governance and ops, The best of modern NLP, Adversarial examples with FGSM + more 🚀mlops · explainability · ml-security #27Jun 2019Distributed AI made easy w Ray, Model Interpretation with Alibi, Principled Machine Learning, Comparing Time Series Models, The quest for high-quality data + more 🚀explainability · reinforcement-learning · mlops #25Jun 2019Google Research on MLOps, The Book on AutoML, Deep Learning for face detection, Maintainable ETL Pipelines, Counterfactuals for Explainable AI, The Semi-Supervised Revolution + more 🚀ml-research · explainability · computer-vision #23May 2019Best practices for ML Engineering, The Journal of Open Source, Visualising Attention in Deep NLP, Pruning API in Tensorflow, ML Explanations with VIBI, Two missing links in serverless + more 🚀explainability · mlops #21May 2019Alibi for black box explanations, Karpathy's tips on training NNs, Nando on learning to learning, A gentle intro to ImageNet, SparkML Kafka Environment, An introduction to computer vision + more 🚀explainability · computer-vision #19Apr 2019Advanced NLP with SpaCy, Grid search across scikit models, A chat on ML version control, Beyond black holes with the code, Scientific python in the browser, XAI v0.0.5 released into the wild + more 🚀nlp · explainability #15Mar 2019AI debiasing doesn't debias bias, The NLP of human noises, Feature visualisation via activation, The GAN stroke of genious, Essential NLP Tools, Code & Tips, AI comedy generated by humans + more 🚀ai-ethics · explainability · nlp #12Mar 2019Bias and Explainability in ML, Federated Learning with PyTorch, Data Visualisation Deep Dive, Practical recommenders tutorial, Learning Curves in ML evaluation, Machine Learning Cybersecurity + more 🚀explainability · privacy · recommender-systems #5Jan 2019XAI - eXplainability library for AI, Deep neural inspection, AI against alzheimer's disease, Differential privacy for tensorflow, The role of ML in databases + more 🚀explainability · ml-security #4Jan 2019Andrew Ng and Reproducibility, 2018 machine learning nostalgia, Magic of Feature Engineering, Explainability/bias with tensorflow, Ensembles and more ensembles, CI/CD for Machine Learning + more 🚀mlops · explainability #3Dec 2018Extreme ML with Kafka, Programming Explainable ML, Computer Vision Everywhere, Beyond Accuracy with ROCs, Super-SlowMo Generators, EC on Trustworthy AI + more 🚀explainability · computer-vision · mlops #1Dec 2018Combat Imbalanced Classes, Compliant machine learning, Data science career transitions, Curiousity driven data science, Automate boring tasks, Facebook open sources PyText + more 🚀explainability · nlp · ml-education