Machine Learning 1: Lesson 12

In the first half of today's class we'll put everything we've learned together to create a complete model for the Rossmann dataset, including both categorical and continuous features, and careful feature engineering for all columns.

In the second half of the class we'll study some ethical issues that arise when implementing machine learning models, and we'll see why they should matter to practitioners, and ways of thinking about them. Many students have told us they found this the most important part of the course!

[GuilhermeLopes-gojb]

Thanks a lot, Jeremy! All the lectures were amazing! This course will probably change my life.

[arashjamshidi]

Thanks for the fantastic course. looking forward to part 2!
I think this course is literally the best machine learning course out there that gives you the "AHA" moment for data science.

[Ekami]

Thanks a lot for this amazing course Jeremy :)

[dovydasceilutka]

I'm very happy that Jeremy talks about the ethics in machine learning and data science. We all should be thinking and talking about it much more.

[michaelbell]

Thank you Jeremy for the fantastic ML walkthroughs (on to your DL course content for me!). Also wanted to thank you for discussing the contemporary ethical issues. For me, transferring to ML + DL from a Psychological Research background, I also have greatly valued the emphasis the social sciences have put on ethics regarding human subjects research. You give clear examples of how ML is significantly affecting the lives of real people, and ML developers MUST get accustomed to considering the possible impacts of their products.

[yassdurr]

almost cried my eyes out at the end! Thank you Jeremy!

[hiirorin]

Just finished the whole course, this lesson makes me think a lot. Thank you, Jeremy, for sharing this. And more importantly, Rachel, for the materials. I am reading the blog posts on fast.ai to get more about the topic. Hope that won't make me too depressed.

[bharatiyanartaki]

The last section of this course is just amazingly put. You make something great, but with caution. Thanks for this course and learning, Jeremy. Been doing both the courses and you're a terrific teacher!

[lagerbaer]

Going back to Lectures 1 and 2 to bring it all together: If we can all agree that more diverse decision trees in a random forest give a better model, then having more diverse human members on your team will give a better team.

[marthawinata]

Amazing work Jeremy, really found the lessons to be insightful and thoughtful

[RANJEETSINGH-trko]

is there part 2 or more of this series ?

[martinbel]

15:00 probably the worst advice ever using notebooks.

[awaisraza]

Can anyone tell me how to setup fastai on google colab?