Відео

good man

Thanks for sharing Matt. However, if you exclusively code in R, what benefit does this offer over the regular Rstudio IDE?

I don't understand how you were able to determine that city and fuel economy were highly correlated from looking at the decision tree?

Thanks for the informative and concise content. I just recently got into R so I'm definitely excited to learn these packages

Great video. Very helpful

Extremely informative and well explained. Thank You!

Hey Matt 👋 Glad to hear that you're enjoying my content. And thank you for sharing my package 🎉

Very profesional! You are my new favorite when it comes to learn data science ⚜️

Many thanks for sharing this R Shiny video tip!

This video is amazing!!! Cant wait for the other parts, how do i subscribe to your newsletter? #bigfan

Nice!

🤯🤯🤯

Thank you so much for taking the time to make this video. You did an amazing job of breaking this all down so that I could understand each step!

Thank you so much for taking the time to make this video. You did an amazing job of breaking this all down so I could easily understand :)

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The ClickFunnels pitch from 2011 makes me want to vomit. Also, no one commented that your optimal channel-mix was Search only? Should have been a massive red flag - no mention of channel incrementality

I did a similar exercise and found that the mean own price elasticity turned out be positive in Random forest for my data. How do I handle it?

Thanks

In 35:00 you said its a tanner feature, well, that is just not true, as far as I know. Putting that 'all_numeric()' is what told your model to not normalize your cat vars...

0 18:20

I perform binary classification using tidymodels and my target variable factor(class, levels = c("Yes", "No")) so my positive class is "Yes" and when predict I want to focus on probability to "Yes". But when I use modelStudio(), the break down and shapley chart show me the probability to "No". Can I change this behavior to show the probability to "Yes"?

what if one wants to calculate the distance from one point to another?

Please show me how to write a SQL temp table in R

Convert jupyter notebook with plotly graphs to pdf

How To do that

I'm sure this is just a matter of me being Git challenged.. but how do I update to get the latest R tips in my project?

I cant use mark code or chunks when im coding in a R extention file? any solutions?

0 18:20

Shiny apps and R are the worst. I am just here so I don't get fired.

Great content Matt! I have learnt a lot and thank you for putting out such detailed lectures.

this is insanely well done :)

notebook: drive.google.com/file/d/19dpLhy4TFml3flJ2a5mbrIzcHdKpKizF/view?usp=sharing , dataset:drive.google.com/file/d/1HQx30IeElFijPosgZGF00c7oVpXazfrB/view?usp=drive_link

Exactily what I am looging for, This problem has bothered me all day，thank you!

Hey Matt, In reg.predict_model, you have included the dataframe that contains the target variable "sales_90_value", isn't it obvious that the model will be easily influenced by this value and predict almost nearest values as the actual values? shouldn't the target variable be excluded from the data when passing it for prediction? Can you please clarify here why you have included it. Thank You😄

Thank you very much man

Thanks a lot for your video. But I have a problem with some of my addresses or postal codes (which all are from Canada). some of my addresses are not in osm so this code will not give me any location for them. these addresses work in google map and google earth. Do you have any solution for my problem?

Thank you really handy! Is there a way to do this but with qualitative variables?

Hi Matt. I wonder if you have the same courses for Python as the ones you have for R. do you? excellent videos!

Great video, thanks for the easy to follow explanations. I have been getting an error once I get to the ARIMA model: Error in `check_case_weights()`: ! 'case_weights' should be a single numeric vector of class 'hardhat_case_weights'. Do you know what it means?

Thank you. This is the reference video I was looking for.

Thank you for uploading this. I'm a new FP&A with some prior experience in R.

I think this approach does not ensure that the part adds up to the whole, does it?

I am enjoying the presentation....what is the link to download the data set: price_optimization.csv?

In excel when we do Trendline linear is it using a ML algorithm? Or the difference between both is the train test split of the data’s which is not done by the user in excel.

what is the vcode color theme? it looks great for presentation. thank you!

Do you also teach how to forecast and create investment or financial asset proforma report?

Thank you for this! :D

thank you, Matt 🙏

Another great video

excellent! ten across the board