Hi All!
I’m super excited about this session. Kaggle Grandmaster Andrada, who is one of the world’s best expert on EDA, storytelling.
In this talk, we will learn about her secrets to making super visual EDA and how you can follow her special sauces. Andrada is truly an amazing speaker and I couldn’t be more excited to bring her back on CTDS 2.0!
Links:
Looking forward to this talk. She is truly an expert in EDA and “data” story telling.
Thanks for having me, can’t wait!
Ok, how do you come up with your analysis, almost like second nature? Is it because you studied Statistics at bachelors? What do you recommend for ppl who are still struggling to come up with more novel arguments without being spoon fed?
I don’t think that young / aspiring data scientists understand the value of SQL.
Can you elaborate on your experience with SQL?
Do you think that SQL skills are valuable in your ability to answer stakeholders questions quickly and easily? did you find these skills also helpful in building ML models at work?
Have you used tools like Tableau / Google Data Studio / Qlik / PowerBI to help you get to know your data? or do you stick with python / R ? or maybe even use Excel?
Also, what are your thoughts on powerpoint skills to help in communicating your message properly to stakeholders?
I feel seen… 
Andrada, what is your favourite Chai?
What is a simple way to for a PhD student into Machine Learning to get into Kaggle Competitions and become Grandmaster? 
Any ML project she would like to work on ? Or any interesting project she is working on these days?
Hey Andrada,
Really appreciate you taking time to walk through your story telling.
How do you structure your EDA where there are a lot of variables in the dataset?
Hi Andrada!
Do you ever find the notebook format creatively restrictive? If you had a blank canvas, what would be your chosen format?
These look very similar to the graph Andrada was talking about. Just wanted to share it here.
As an Undergrad Statistics student, I recently got into coding and kaggle. frankly, I find ML and DL concepts a little overwhelming but by hearing this talk I am highly motivated to start contributing to kaggle via EDAs and visualizations.
could you please suggest references /courses that may help me start my Kaggle journey?
I’d like to respectfully disagree with the push for D3. It is much more suited for data journalists, not data analytics in a business setting … when you need to answer your boss and other business stakeholders, nobody will want to wait for 1 to 2 to 3 weeks for us to perfect it in d3.
the value for analytics in the ML space is … instead of feeding your finding or viz into a report, you feed those values as a feature into an ML model right? I don’t see a place for D3 unless you are trying to be a data journalist or trying get upvotes on a EDA notebook. it just isn’t practical.
We can use power BI & Tableau, Looker.
I will shamelessly promote myself here, but this is step by step what I did: Get Started with Data Science | Data Science and Machine Learning | Kaggle