I recently got access to OpenAI's DALL·E 21 text-to-image beta. In short, this AI system can generate images from text prompts, create semantic local edits by selecting an image region and altering your prompt text, or generate variations of uploaded or generated images.
I've been playing with it and will be doing a live demo today in Live 79 and sharing some of my experiments and thoughts on this tool, which is quite impressive.
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In Live 70—I learned about YouTube's Upload Python API, which allows us to programmatically upload high-resolution videos to YouTube from a client application or the command-line interface.
Among other things, we learned how to create a Google Cloud Platform project and create API keys and OAuth 2.0 credentials to authenticate custom applications to different Google APIs. We also saw how to restrict your client id and secret to a specific IP address during testing and how to scope our application to certain API calls (say, uploading videos to YouTube or changing video thumbnails).
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In yesterday's live stream—Live 68—we took a look at the linear regression following Aurélien Géron's Hands-On Machine Learning book. We saw the normal equation, how to calculate the dot product of two matrices and the inverse of a matrix, and saw a few different ways in which, with code, you can solve a linear equation, plus how to do it with Sci-Kit Learn's LinearRegression
class.
You can take a look at the Linear Regression Colab notebook.
Use the timestamps below to jump to specific parts of the stream.
If this is something that interests you, please let me know on Twitter or, even better, on the Discord community.
Thanks for watching.
See you next week!