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.

You can now propose live stream and podcast topics at topics.nono.ma. Suggest a topic and explain why it would be interesting to cover it on a YouTube live stream or the Getting Simple podcast.

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).

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!

Chapters

• 02:30 Introduction
• 04:29 Getting Simple
• 06:11 Goals
• 07:32 Today
• 08:33 YouTube Upload Python API - Intro
• 09:14 YouTube Upload Python API - Outro
• 09:34 Interlude
• 11:10 YouTube Account and API
• 13:00 Obtaining Authorization Credentials
• 16:54 Create a Project
• 19:13 Q: What is something you enjoy doing outside work?
• 19:53 Create a Project
• 21:46 Create API Keys
• 30:38 Enabling the YouTube Data API
• 35:10 Client Libraries
• 36:10 Python Conda Environment
• 39:19 Install the Google API Client Library for Python
• 44:18 Updating Samples to Python 3
• 47:20 Set Up OAuth Authorization
• 47:33 Consent Screen
• 48:59 API Scopes
• 52:06 Test Users
• 53:22 Create OAuth Client Id and Secret
• 54:48 Break
• 01:00:09 Video Upload Command
• 01:06:12 Sample Video Upload Request and Authorization
• 01:10:57 The Video Was Uploaded!
• 01:13:26 Upload a Public Video
• 01:14:35 You Can Upload 2K and Other High-Resolution Videos
• 01:15:23 Outro

Hi, all! I'm a bit behind with adding chapters and summaries about what we did in the live stream, specifically for Live 70 and 71—I'm working on it! There won't probably be live-streaming the first week of May (that's this coming week). But it seems we'll be back at it on Thursday, May 12.

You can watch my three-minute summary of Live 71.

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!

Chapters

• 2:05 Introduction
• 4:57 Blog
• 5:42 Thoughts on streaming and podcasting
• 9:40 Digital art experiments with p5.js
• 15:31 Plotting a linear equation
• 22:30 Linear regression and matrices
• 33:13 DALL·E 2
• 41:25 Matrix dot product
• 48:40 Inverse of a matrix
• 53:48 The normal equation
• 1:00:24 Linear regression with Sci-Kit Learn