Elena SamuylovainTowards Data ScienceMonitoring unstructured data for LLM and NLPA code tutorial on using text descriptors14 min read·Jun 27, 2023----
Elena SamuylovainTowards Data ScienceHow to Measure Drift in ML EmbeddingsWe evaluated five embedding drift detection methods10 min read·Jun 14, 2023--4--4
Elena SamuylovainTowards Data ScienceMonitoring NLP models in productionA code tutorial on detecting drift in text data13 min read·Feb 20, 2023--6--6
Elena SamuylovainTowards Data ScienceMonitoring ML systems in production — which metrics should you track?When one mentions “ML monitoring,” this can mean many things. Are you tracking service latency? Model accuracy? Data quality? The share of…24 min read·Jul 18, 2022----
Elena SamuylovainDeepnoteEvaluating Data Drift and ML Model Performance with Evidently and DeepnoteHow to quickly build beautiful interactive reports on your model.4 min read·Dec 14, 2021----
Elena SamuylovainTowards Data Science“My data drifted. What’s next?” How to handle ML model drift in production.An introductory overview of the possible steps.16 min read·Dec 1, 2021--2--2
Elena SamuylovainTowards Data ScienceWhat is the difference between outlier detection and data drift detection?Explained simply6 min read·Nov 8, 2021--1--1
Elena SamuylovainTowards Data ScienceA Machine Learning Model Monitoring Checklist: 7 Things to TrackHow to monitor your models and which open-source tools to use7 min read·Apr 19, 2021--1--1
Elena SamuylovainTowards Data ScienceMachine Learning in Production: Why You Should Care About Data and Concept DriftNo model lasts forever. Even if the data quality is fine, the model itself can start degrading. What does this mean in practice?10 min read·Dec 7, 2020--7--7
Elena SamuylovainTowards Data ScienceMachine Learning Monitoring: What It Is, and What We Are MissingIs there life after deployment?11 min read·Sep 10, 2020--2--2
