Відео

list in python is also a stack

Just getting adict to your contens now. Sharp and easy to follow. Thank you very much

Amazing

very usefull

Rob, are you aware that you have made a crucial forecasting mistake? You used the test set for validating the model when fitting, then you used the same test set when you made the final predictions and evaluated it on the same set. The problem is that during the fitting, the model gets to see the test set so you have data leaked into the past, from the future. What you should do is to split the data into train/val/test where the test has never been seen by the model.

You are trying too hard

What about using these cross validation objects within GridSearchCV, how would you treat the creation of new features for each fold? Would you have to sacrifice using GridSearchCV to be able to apply feature engineering with aggregate data on each fold? Your approach allows feature engineerimg on each fold, but it does not allow the benefit of hyperparameter tuning as with gridsearchcv. Would the best advice be to use your approach of cross validation and apply in each fold loop with feature engineering, but with the drawback of relying on manual hyperparameter tuning instead f methods as gridsearchcv or randomsearchcv?

Really must watch video. I must say that I really like the way you explain things, it's so easy to understand and follow along. Thank you!

Amazing. Really covered very well most of my questions from the firat video. This is the best video I have seen so far about xgboost that integrates time series data with feature engineering that uses aggregate data and shows clearly how to use it with cross-validation appropriately to avoid data leakage. I would make a 3rd part where you focus on integrating everything within a preprocessing pipeline along with hyperparameter tuning using GridSearchCV or any other method in order to make it more robust. Either way you showed me a new way to use

Thanks! U remember me about enumerate function❤

Thanks so much for this video. It would be cool as well to see a video with xgboost mainly about feature engineering using aggregate data(for example the average of the last 30 days) while using cross validation appropriately to avoid data leakage. Would hyperparameter tuning with GridSearchCV would have to be sacrificed since you can't easily control creating these features using aggregate data within each dataset split made in the cross-validation? Thanks so much for your enlightening and amazing videos. I highly appreciate your work.

Linear regression is a bad choice for this kind of data. This is a time series problem. cumulative sums introduce autocorrelation between datapoints, which violates the assumption of iid residuals of linear regression. Code ok, reasoning not.

i think predict forecasthing not suitable with XGboost model, because xgboost just using method like decision tree (it's not interpretation), if you want using machine learning I recommend using deep learning like LSTM, GRU, RNN

how can an external LaTex file be called/included/embedded in a JupyterLab cell?

What does the max function do? Doesn’t each video have a single view count?

Where is or where to take the dataset

Hello again

Don't watch. Waste of time. The whole video is just import timm; timm.Model().forward();

Don't watch. Waste of time. The whole video is just import timm; timm.Model().forward();

Your shared videos are fantastic, Rob. Well done. By the way, I applied the above, but I was unable to scrape the data, assuming that Twitter does not allow escape without API. If anyone has done this successfully, please advise.

You robbed my precious 2 hrs rob mulla. I watched your How to Pytorch video hoping you'd show me how to build a model using Pytorch. Then I watched this video as well. Thanks for scamming me of my precious time and attention. You just showed how to import timm and call forward() on it. You didn't teach me how to make a model using Pytorch. Thank you so much 🙏 keep stealing everyone's time.

Woops I’m a double noob

Amazing video, you made it so simple

Sorry to say but you should give more details about how you the process.

Ah yes, writing unconventional code which can't be found in other mains stream languages is somewhat less noob than writing some code which is already clear and can be written in most languages Truly stupid -_- don't call people noob, it's a noob thing to do

In general indexing is slow in df numpy faster

if you are facing error at 4:41 try pd.set_option('display.max_columns',200) instead of pd.set_option('max_columns',200)

ways_to_code = ['range', 'counter', 'enumerate'] noob = 'Stop Doing It This Way' for funny_jokes in ways_to_code: if funny_jokes == 'range' or funny_jokes =='counter': print(noob) else: print('Okay, you\'re alright')

Rob please don't stop making videos. I just discovered your channel and my universe just expanded!!! Awesome stuff!

hey, does deepface work without the internet? like can i install it on a machine, then unplug my ethernet cable, and it will still work or does it need to talk to the cloud somehow?

This video came many times in my home page recommendation but i was ignoring cause it's just a 22 min video.....but boom 🤯 ! Omg not even a 2 hours video of others cover all these.❤ thanks

Can this talk with, summarise; and analyse excel or csv files?

I know ur sons name is Daniel

ur kids name is daniel

ur not safe

they live in potomac maryland

ur kids name is daniel

Thanks. Easy to follow you.

Do you code in python... learn a real language like C and C++... Then go back to python and you will be irritated relentlessly by the loosely typed nature of the language and you will go back to C because it makes you feel like a boss

Better we can pass the value into ChartJS and create whatever you want. It's been 2 years, I try to build a good dashboards using flask, I never find any good solutions yet.

Learned a lot, subscribed 🤙🏻

Don’t ducking judge me. I identify as a professional👍

Just brilliant! Thank you so much!

Thanks can I ask what editor do you use?in this video

I really hate these stock video interruptions

hii can i do the same in jupyter notebook? as i work on that

You got me at "I'm a data scientist"

So if i change my code tomorrow I won't be a double noob anymore?

Thank you Rob!! Very nice explanation of Jupyter options and environments!

I loved it. Thank you.