This book helped me crack my ML interview at Goldman Sachs...
I have been getting great response on my posts lately so decided to share one of the most important books on Optimization algorithms that helped me crack my interview at Goldman. Mykel J. Kochenderfer and Tim A. Wheeler have done a greta job explaining some of the toughest concepts in Mathematical optimization and they have implemented the code in Julia which is super fun to code along.
Next post on AI will come when this post gets 50 likes.
Sharing the link to the book here, it covers some of the most foundational topics in optimization.
Talking product sense with Ridhi
9 min AI interview5 questions
What will you do with those 50 grapes?
@ElonMast nothing wrong with some free internet points. Atleast I know someone got value out of this.
Not doubting the value link has, but really curious to know about grapes accumulation.
Did you actually?
Based on your previous posts in this community, I am starting to doubt your credibility.
I could be wrong.
Yeah focused too much on accumulating grapes.i share the research paper findings as well. But I don't share it on grapevine , because people can easily find my identity via LinkedIn since I started to post weekly there.
So every time you add these resources, could you please add the questions that were asked pertaining to that resource? It’d be really beneficial for the community.
Thanks!
Can I DM, looking to crack DS role but not encouraging results.
Have a mix of DS and analytics experience
we finally got someone from DS community being this active and sharing such helpful resources. 50 grapes no big deal 🤝💯
Curious about your role at GS Is it more on the statistical modeling side or GenAI side? As it is a financial institution
And pretty soon long work hours coming!
Hello, looking for a referral at Goldman Sachs.
What do ML engineers do at investment banks like GS?