Life of an AI project - MFML Part 2

[@Lalalacici]

Absolutely amazed by how much you have simplified these concepts and still maintained the details, hats off.

[@blakebassett2408]

This is the most approachable, comprehensive machine learning content I've seen. The analogies are powerful, useful, and applicable. I also appreciated your emphasis on the important role played by cross-functional teams of human decision-makers and qualified 'Wish Makers.' The human element, I've found, is often overlooked and unappreciated. Thanks for sharing!

[@xyx982]

5⁵

[@xyx982]

⁵

[@mohamedzeineldin913]

Data science introduced as Ballet Dance! well done

[@mitya7068]

It is true that the terminology can be really confusing whereas the actual thing it refers to could be simply explained even to a child. Thank you for the great material!

[@davidyolchuyev2905]

I love the content that you share on youtube. Thanks Csasie

[@vpratapify]

Amazing content, the most simplified way of teaching I have encountered so far.

[@tyagianujk]

You make it so intuitive and fun! Thank you.

[@nikmithani1337]

Very well done. View count and comment count suggest that ML and AI is still too challenging for most.

[@anandpbgupta]

This is really great content and I am truly inspired by it! Are any notes, blog post or slide deck available for quickly referencing the content for future use?

[@dzivkovi]

I p

[@HardikMahendru]

28:01 : Most imp first step 37:42 : Did it get it right or not?, did it found a cat? Precision vs recall is very important 1:21:04 : It is most important line for Applied ML. How long does each one take to try.

[@nehverma2489]

Cassie such a wonderful way to explain, I am clear about each and everything. Thank you.

[@maxalonzo3716]

Thanks for sharing this content Cassie, this is very inspiring to get to present ML to non tech persons :) Sharing it right now

[@simplemente_humano]

Excellent content! Thanks for sharing!

[@deolindoximenes3165]

Couldn't be better! Well articulated :)

[@boontecksim8531]

SPLIT YOUR DAMN DATA!! Point taken lol. Loving the content.

[@Abdullahkbc]

Thanks Cassie, waiting for new content from you.

[@parrotraiser6541]

George Babbage was asked by an MP (funding his Difference Engine) "If the machine is given the wrong numbers, will it return the right answer?". By the sound of it, decision-makers haven't improved over a couple of centuries.

[@Bloodlion1972]

Where can the presentations be found ?

[@blue_slushy9]

her laptop stickers are dope af

[@frisonalberto]

Cassie can we have the slides somehow? thank you!

[@GameRunner2049]

Thank you !

[@abuhelweh]

I like your voice, I can hear you all day and night

[@rafaeldeconti]

Cat, or not cat, and the tiger. Now, think about how we get intuition about numbers. 5 digits of the hand, 3 the leaf clover, 2 wings of the bird...the 5 can be saw on 5 cats, the 3 in three units of cats, the 2 on two cats and so on...what I mean? About generalization...this power to generalize, acquire something that is a pattern among the things, we, humans, can do trough some examples...the machine can do from more examples (data)...what are the patterns that the AI had discovered and that we, humans, can not see? Some examples?

[@0MoTheG]

Not dog, not dog, not dog, not dog I feel dogs are underrepresented, this is systemic.

[@jasonsykes4199]

Programmers were simulating before staticians thought it was cool. ;)

[@Tiago_R_Ribeiro]

1:22:50

[@rafaeldeconti]

Are we, humans, training AI with "No CAPTCHA reCAPTCHA"?