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MindsDB and DataTalks.club hosted an online hands-on workshop on September 21st 2022, about machine learning inside data-layer.
As an ML engineer, you want to live in a world where you can manage exploration, training, versioning, and inference from one control plane. In-database ML has the potential to make that real.
In this hands-on workshop, we’ll go through all the steps from data preparation, tuning and deployment of custom models with the ML frameworks of your choice through SQL and declarative ML.
We will use MindsDB, an open-source in-database ML platform, that allows developers and data professionals to use the power of AI to ask predictive questions of their data and receive accurate answers from it - in a simple way. Customer behaviour, revenue maximization, production optimization, churn or demand predictions are just a few mission-critical use cases you can easily implement with MindsDB right where your data lives.
We’ll cover the following topics:
And more
By the end of this workshop, you’ll be able to set up an in-database ML pipeline yourself.
Patricio Cerda-Mardini, Machine Learning Research Engineer @ MindsDB
Since joining MindsDB in 2020, Patricio has become the core maintainer of its in-database predictive ML engine. His research interests include deep learning forecasting and model-agnostic calibration methods. His academic degree is focused on human-robot interaction and recommendation systems, areas in which he holds several publications.
LinkedIn: https://www.linkedin.com/in/paxcema/
Twitter: https://twitter.com/paxcema
Website: https://mindsdb.com
MindsDB and DataTalks.club hosted an online hands-on workshop on September 21st 2022, about machine learning inside data-layer.
As an ML engineer, you want to live in a world where you can manage exploration, training, versioning, and inference from one control plane. In-database ML has the potential to make that real.
In this hands-on workshop, we’ll go through all the steps from data preparation, tuning and deployment of custom models with the ML frameworks of your choice through SQL and declarative ML.
We will use MindsDB, an open-source in-database ML platform, that allows developers and data professionals to use the power of AI to ask predictive questions of their data and receive accurate answers from it - in a simple way. Customer behaviour, revenue maximization, production optimization, churn or demand predictions are just a few mission-critical use cases you can easily implement with MindsDB right where your data lives.
We’ll cover the following topics:
And more
By the end of this workshop, you’ll be able to set up an in-database ML pipeline yourself.
Patricio Cerda-Mardini, Machine Learning Research Engineer @ MindsDB
Since joining MindsDB in 2020, Patricio has become the core maintainer of its in-database predictive ML engine. His research interests include deep learning forecasting and model-agnostic calibration methods. His academic degree is focused on human-robot interaction and recommendation systems, areas in which he holds several publications.
LinkedIn: https://www.linkedin.com/in/paxcema/
Twitter: https://twitter.com/paxcema
Website: https://mindsdb.com
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