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Tutorials

Machine Learning Tutorials

lakeFS-spec: An Easy Way To Work With lakeFS From Python

Jan Willem Kleinrouweler, appliedAI, Max Mynter, appliedAI

TL;DR In this blog post, we will explore how to add data versioning to an ML project; a simple end-to-end rain prediction project for the Munich area. The data assets will be stored in lakeFS and we will use the lakeFS-spec Python package for easy interaction with lakeFS. Following model training with initial data, we […]

Data Engineering Machine Learning Product Tutorials

Introducing The New lakeFS Python Experience

Oz Katz, Nir Ozeri

Since its inception, lakeFS shipped with a full featured Python SDK. For each new version of lakeFS, this SDK is automatically generated, relying on the OpenAPI specification published by the given version. While this always ensured the Python SDK shipped with all possible features, the automatically generated code wasn’t always the nicest (or most Pythonic)

Data Engineering Machine Learning Tutorials

Unlocking Data Insights with Databricks Notebooks

Idan Novogroder

Databricks Notebooks are a popular tool for interacting with data using code and presenting findings across disciplines like data science, machine learning, and data engineering. Notebooks are, in fact, a key offering from Databricks for generating processes and collaborating with team members thanks to real-time multilingual coauthoring, automated versioning, and built-in data visualizations.  How exactly

Data Engineering Machine Learning Tutorials

AWS Trino and lakeFS Integration

Amit Kesarwani

A Step-by-Step Configuration Tutorial Introduction In today’s data-driven world, organizations are grappling with an explosion in the volume of data, compelling them to shift away from traditional relational databases and embrace the flexibility of object storage. Storing data in object storage repositories offers scalability, cost-effectiveness, and accessibility. However, efficiently analyzing or querying structured data in

Best Practices Tutorials

The Power of Databricks SQL: A Practical Guide to Unified Data Analytics

Oz Katz

In the universe of Databricks Lakehouse, Databricks SQL serves as a handy tool for querying and analyzing data. It lets SQL-savvy data analysts, data engineers, and other data practitioners extract insights without forcing them to write code. This improves access to data analytics, simplifying and speeding up the data analysis process.  But that’s not everything

Best Practices Machine Learning Tutorials

ML Data Version Control and Reproducibility at Scale

Amit Kesarwani

Introduction In the ever-evolving landscape of machine learning (ML), data stands as the cornerstone upon which triumphant models are built. However, as ML projects expand and encompass larger and more complex datasets, the challenge of efficiently managing and controlling data at scale becomes more pronounced. These are the common conventional approaches used by the data

Best Practices Data Engineering Tutorials

Databricks Unity Catalog: A Comprehensive Guide to Streamlining Your Data Assets

Oz Katz

As data quantities increase and data sources diversify, teams are under pressure to implement comprehensive data catalog solutions. Databricks Unity Catalog is a uniform governance solution for all data and AI assets in your lakehouse on any cloud, including files, tables, machine learning models, and dashboards. The solution provides a consolidated solution for categorizing, organizing,

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