Join 📚 Kevin's Highlights
A batch of the best highlights from what Kevin's read, .
**Are you aware of the risks?**
You need to know about the reasonably foreseeable risks and impact of your AI product before putting it on the market.
If something goes wrong – maybe it fails or yields biased results – you can’t just blame a third-party developer of the technology.
And you can’t say you’re not responsible because that technology is a “black box” you can’t understand or didn’t know how to test.
Keep Your AI Claims in Check
Federal Trade Commission
• Finding and Understanding the Data
• Cleaning the Data and Feature Engineering
• Tuning and Evaluating
• Using the Model and Presenting Results
The Machine Learning Process
Codecademy
Here's something I've learned
over the past five years of blogging:
don't start by telling the audience
why you wrote a blog post.
Instead,
tell them why they should read it, and
then do your best to prove yourself right.
Technical Writing for Developers – Why You Should Have a Blog and How to Start One
Ankur Tyagi
...catch up on these, and many more highlights
Readwise