Video

Pls mic fix

I am a PhD candidate in data analytics looking for job for eight months right now not even a single interview it’s very tough😫

That was a really good explanation. Short and powerful.

I used Python during my PhD and ended up shifting to R. Python's statistical packages are lackluster (maybe not surprisingly). I'm not a big fan of dot chains and pandas' index system, and the deal breaker was that it was so sluggish and busts memory so often with medium size data (20GB+) even with 60GB+ RAM machine. Tried Dask but it's pandas based and slow - with duckDB / polas I think dask project will be less popular. I picked up tidyverse and data.table from R, and it did the job without a problem, and I kinda regretted learning Python. R has fixest package that is really fast for high demensional fixed effects regressions, and python doesn't seem support large scale regressions very well.

R is more capable of doing amazing things better than python

I am AWS ML certified

Good to hear that you learnt R and then created the video. I can understand @6:41 - After learning c , c++, basic , cobol ie having a programming background. R really felt funny and weird because there are multiple ways you can do the samething. But later i fell in love with R . I have heard numpy and pandas are inspired from R datastructures. You have computer engineers backing up development and usage of python whereas bunch of academicians and statisticians for R. R initially looked like hotchpotch but after looking at numpy and pandas with basic python...... i just laugh at my judgements reversing over time. Python seems to be more in line with traditional expectation from OOPS syntax...i can go on ..... but both could have been more streamlined for the workflow of datascience

I can't believe FORTRAN is #12! I programmed my master's thesis project in 1995 in FORTRAN and I thought nobody used it anymore. As a statistician I'm guessing R is the way to go.

Nice honest and informative video. Thank you.

helpful video , thank you sir 🌟

It remains vague. What exactly can you do with R that is not possible with Python?

I like how you present the data/ideas 😂... Thanks for the information ❤

I dislike videos that make reproducibility challenging. You could demonstrate the exact same concepts using a simple data frame that can be found in seaborn (or any other imported package for that matter). Nice video otherwise

good.mugo on data

how do you LEARN this stuff -- I mean really LEARN -- I took a course in biostatistics where we covered this and for every problem I had to keep referring back to a page where I had written all the formulas -- there was no way I could tell you the formula for specificity or sensitivity -- I understood the consequences and reasons for them (telling someone they have diabetes when they don't leads them to spending money on drugs they don't need) -- but as for applying the correct measure and formula to every scenario I was totally lost -- if we weren't allowed to use a page of formulas for the final I would have failed spectacularly

Thanks Richard, that was a good overview of classification metrics.

good.mugo on data

For me the greatest difference between the two languages is the mentality. R users are taught basic programming fundamentals and learn that for every solution there is a package they can use. Python users are taught programming first and how the language is used to create packages. So R users learn to use the language at a higher level, and when they go deeper then things get messy. Also in 2024 I wouldn't keep putting labels such as R for statistics and Python general purpose etc. This kind of labels is absolutely nonsense.

Nice one! This is a topic I need to start getting into. Would love more content on XAI!

Awesome, instead of Python, can this be done using R

Thanks for the great video! Should i reverse the remotesigned execution policy after finishing the install and setup, or does it have to stay on Y permanently?

This was awesome. Thanks. I’m gonna go see how I can apply these when presenting to stakeholders

You are awesome bro, thanks

Well damn 1yr left to learn

How many weeks or months did you take to study for the exam?

My university economics program uses R. I learned both for obvious reasons

Thanks for the great video. it was an awesome comparison. Are you practicing data science, I am looking for small role in data analysis with R programming software, do you have any advice. I have a masters degree in environmental science from Addis Ababa University. By the way are you on LinkedIn, would like to follow you. Thanks.

Hi Sir thanks for yet another great video. can you make a video on the most widely used ML tools. I have a background of chemistry and Environmental science on a masters level, I have started learning r through reading book and watching you tube videos. do you think I have a future on data science. I'm from Ethiopia.

Video of my wish😂

that data dictionary does seem useful, I would be curious to see how well it deals with more " disguised" features, such as a categorical feature that seems continuous or the inverse. Because sometimes I feel getting the feature type right can really be a matter of knowing, it would be impressive if it was very consistent.

Stopped using ai, as I stopped learning and got lazy. Now only reach for it as a last resort.

I'm a newbie of R and I like it. Thanks for the great video.

Thanks for this breakdown . I am graduating from a master's in analytics in a few months and this video came at the right time

this nigga is a genius

Great and relevant content. Thanks my pal.

i like R

I got admitted to MSDS in MSU. Can you tell me some relevant course work that I should take to get into data engineering?

Thanks

If you're in healthcare or pharma, the other language to know is SAS. I know, it's old hat, but it has a simple syntax, a rich macro language and it is certified for use in FDA-regulated industries.

Has this helped with making any transitions to MLE? Have you noticed companies caring?

Thanks, Richard! Great video.

How to decrease the size of the column?

Julia is the light and the way

Welcome back!

Thank you for this. Very informative.

You mention at the initial stages getting a degree in a related area but what about folks who have education and experience in a different area. For example, what if a designer or lawyer wants to get into the data field. What would your recommendations be for such people to build their knowledge and get their foot in the door ?

Very good summary. Thank you!

please share your linkedin