Learn how to develop, deploy and iterate on production-grade ML applications.
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End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
Free MLOps course from DataTalks.Club. Register here 👇🏼 to get notified about the next cohort
- machine-learning
- mlops
- model-deployment
- model-monitoring
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
- data-drift
- jupyter-notebook
- pandas-dataframe
- machine-learning
Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
- data-science
- python
- dag
- data-engineering
Slides, scripts and materials for the Machine Learning in Finance Course at NYU Tandon, 2022
- coursework
- fraud-detection
- introduction-to-machine-learning
- machine-learning