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Machine learning in real life

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Nastasia Saby

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Previous issues:

Issue 16: A story of distributions (26th of June, 2021)

Issue 15: Designing Data Intensive Applications (3rd of June, 2021)

Issue 14: Market yourself, ACID transactions in DeltaLake, OpenSource and Bayesian ABTests (27th of May, 2021)

Issue 13: Kubernetes and DevOps concepts (13th of May, 2021)

Issue 12: Bayesian AB tests (29th of April, 2021)

Issue 11: Machine Learning Design Patterns (1st of April, 2021)

Issue 10: Challenges in Deploying Machine Learning (18th of March, 2021)

Issue 9: Code standardization, container orchestration, lakehouse, cats: concepts needed to productionalize machine learning models (4th of March, 2021)

Issue 8: Code standardisation and MLOps seen by Databricks (18th of February, 2021)

Issue 7: Recommender systems and data engineering (4th of February, 2021)

Issue 6: The past, present and possible future of AI and ML (21st of January, 2021)

Issue 5: Resources to get started with Kubernetes (7th of January, 2021)

Issue 4: Resources to get an overview of a machine learning project (24th of December, 2020)

Issue 3: Feature store, weird chatbot, XGboost for Spark and Airflow in Amazon (10th of December, 2020)

Issue 2: Unit tests for data, Data + AI summit, etc (26th of November, 2020)

Issue 1: Data versioning, tips for Pytest, freelancing, etc (12th of November, 2020)

Nastasia Saby