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Unleash AI power
With MySQL + MindsDB
AI is useful for everyone
Examples of predictions that many companies need:
● Sales (next year, in a store with certain characteristics…)
● Cost of providing a service
● Cost of IT infrastructure
● Website or app usage
● Disasters
But implementing Machine Learning is not easy
Machine Learning
The steps are (approximately):
1. Identify the problem
2. Understand the data to use
3. Prepare data
4. Train model
5. Evaluate model performance
6. Experiment with real data
7. Repeat some or all the steps above
Machine Learning
● Step 3, Prepare data, is particularly complex:
○ Extract data from the source
○ Cleanse data
○ Aggregate data
○ Label data
○ Transform data
Machine Learning
● And which people do you need to do all this?
At a minimum:
○ Data engineers to make the data available to:
○ Data scientists to create a model, train and test it
○ Marketing people who understand the data and need the
predictions
Machine Learning
● MindsDB enormously simplifies the process!
MindsDB
● You connect it to external data sources (integrations)
MySQL, MariaDB, PostgreSQL, Cassandra…
Apache Hive, Ignite…
OpenAI
Google Analytics
Paypal
Hubspot
OpenStreetMap
…
MindsDB
● You run SQL queries about the future, or other missing data
SELECT * FROM sales WHERE date > '2024-02-01';
MindsDB
● MindsDB predicts the missing data. Many AI engines are
available to do this
Lightwood, PyCaret
TimeGPT
LightFM, Polars
Replicate (images, videos)
…
MindsDB
Why to use SQL?
● Easy to read and write
● It's been around since forever, still evolving
● Lingua franca for both humans and machines
MindsDB
● At Vettabase, we're proud to be the maintainer of
the MySQL MindsDB integration
● We made some usability enhancements, more will follow:
○ To connect MySQL a URL can be specified
○ Port is now optional (3306)
○ A query timeout can be specified
● We wrote a beginner article on MindsDB + MySQL
MindsDB + Vettabase

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Webinar - Unleash AI power with MySQL and MindsDB

  • 1. Unleash AI power With MySQL + MindsDB
  • 2. AI is useful for everyone Examples of predictions that many companies need: ● Sales (next year, in a store with certain characteristics…) ● Cost of providing a service ● Cost of IT infrastructure ● Website or app usage ● Disasters But implementing Machine Learning is not easy Machine Learning
  • 3. The steps are (approximately): 1. Identify the problem 2. Understand the data to use 3. Prepare data 4. Train model 5. Evaluate model performance 6. Experiment with real data 7. Repeat some or all the steps above Machine Learning
  • 4. ● Step 3, Prepare data, is particularly complex: ○ Extract data from the source ○ Cleanse data ○ Aggregate data ○ Label data ○ Transform data Machine Learning
  • 5. ● And which people do you need to do all this? At a minimum: ○ Data engineers to make the data available to: ○ Data scientists to create a model, train and test it ○ Marketing people who understand the data and need the predictions Machine Learning
  • 6. ● MindsDB enormously simplifies the process! MindsDB
  • 7. ● You connect it to external data sources (integrations) MySQL, MariaDB, PostgreSQL, Cassandra… Apache Hive, Ignite… OpenAI Google Analytics Paypal Hubspot OpenStreetMap … MindsDB
  • 8. ● You run SQL queries about the future, or other missing data SELECT * FROM sales WHERE date > '2024-02-01'; MindsDB
  • 9. ● MindsDB predicts the missing data. Many AI engines are available to do this Lightwood, PyCaret TimeGPT LightFM, Polars Replicate (images, videos) … MindsDB
  • 10. Why to use SQL? ● Easy to read and write ● It's been around since forever, still evolving ● Lingua franca for both humans and machines MindsDB
  • 11. ● At Vettabase, we're proud to be the maintainer of the MySQL MindsDB integration ● We made some usability enhancements, more will follow: ○ To connect MySQL a URL can be specified ○ Port is now optional (3306) ○ A query timeout can be specified ● We wrote a beginner article on MindsDB + MySQL MindsDB + Vettabase