One of the big challenges with computer vision machine learning projects is performing training.
Why is it challenging?
Because historically it's been a very manual process thats time consuming and costly, but I've got some good news for you. You might be able to automate your training process with a new tool called Autodistill. Checkout this video to learn more.
Historically the cost of performing computer vision training has been expensive and often prohibitive but with Grounding Dino, you might be able to skip the training step. Watch this video to see how Grounding Dino, a Zero Shot Object Detector, performs object detection without custom training.
There are many interesting things you can do with computer vision, including detecting custom objects. In this video, we look at how to train a computer vision algorithm (YOLOv8) to detect custom items.
In this video, we demo computer vision at the edge using Mycelial to store data locally and send it back to the cloud. We’re using Mycelial to get a computer vision model to the edge where we are then doing inference and data storage locally and using Mycelial to move data back to the cloud (Snowflake in this case). This means that the computer vision inferencing will continue to run even if the network connection is lost. We can then trust that Mycelial will synchronize the data to the cloud when network connection is restored. This has a couple crucial advantages over sending all your data back to the cloud for processing, which we discuss in the video.
There are many ways to backup an SQLite database, watch this video to see all the options, along with the preferred options.
Clustered Indexes (WITHOUT ROWID optimization) are a special optimization you can make that could make your queries twice as fast and it could save on disk space as well.
Check out this video to learn more about this optimization.
Database statistics are a set of data that provides information about the distribution of values within a database. This information is used by the database management system to make informed decisions about query optimization and to improve query performance.
Want to learn more about statistics in SQLite? checkout this video.
SQLite doesn't have date and time datatypes, which begs the question, how do you deal with your date and time values?
Want to learn more? Check out this video.
A Common Table Expression (CTE) in SQL is a named temporary result set, derived from a SELECT statement, that can be used within another SELECT, INSERT, UPDATE, or DELETE statement. It is defined using the WITH clause followed by a SELECT statement and a name for the CTE, and can be referred to by name in the main query. CTEs are useful for breaking down complex queries into simpler, more readable parts, and can also improve query performance by reducing the need to repeat subqueries.
Want to learn more, check out this video.