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I will be making an hourly passenger count forecast using LSTM time series model with 6-7 parameters. Can I choose the parameters as you did here?

I want to make LSTM time series, what should I do for this? I think the situation is different for time series. Would I be wrong if I use what you did? There is both trend and seasonality in the series.

Amazing video and excelent didatic. Congrats for the great quality, helped me a lot!

Seriously this channel is amazing, you deserve so many more subscribers man!

Wait, just realized you are such a small RUclipsr. Thought you would have at least 200,000 subscribers with this quality video. Explaining everything in depth and very understandable with very helpful and educational videos!

Marco's the man!

Very interesting explanation and clear to understand. I was looking for this kind of tutorial. Subscribed👍

I like the logic of this video. You showed the baseline, then three additional methods, then compare them in the end. Thanks a lot for sharing the technique. The feature/target matrix is also very helpful. My question is the principle or concept behind the filter method, RFE, and boruta. Is it possible to do a video on them?

subscribed

Hugely informative and educational content. Many feature engineering videos are not that instructive.

Hello!! quick question, why is the threshold 3.5 any reason please?

It was great! Thanks for sharing your knowledge. Hope to see more of you.

Do you have LinkedIn? Could I follow you? : )

Please do more Data science-related content, It was very helpful I searched everywhere for feature selection videos and finally landed on this video and this was all I needed, the content is awesome and the explanation is as well!

I am a noob to data science and feature selection. Yours is the most succinct and clear lesson I have found... Thank you!

I thought feature selection is done before model training. Am I wrong?

Thank you so much, you are my life saver !!

how about random cut forest ?

Very interesting content, thank you!

Thank you for sharing

Sensational video, thank you so much!

nice and clear

Dear Marco Thank you.😀

Hi! Do you recomend any video for pattern-wise anomaly detection?

Hello Marco, thank you so much for such a great video. Can you please make a video on anomaly detection for time series data using pycaret.

Awesome video

Excellent video, however I'm preoccupied trying to figure out if having wine as a gas would make dinner parties better or worse. 🤔

Thank you! It's helpful!

Merci Marco pour le partage !

🎉 thank you a lot

Hi Marco!! Thank you so much for making great videos on "Anomaly detection". Great Great work! Please keep sharing! 🙏🙏🙏🙏

in Variance threshold technique, if we use Standard scaler instead of Minmax scaler, the variance would be the same for all variables.... does it means we can eliminate this step and just use standars scaler?

Wow, this video is really helpful, a lot of interesting methods were shown. Thanks a lot. I like to ask you to make a future video covering how you perform feature engineering and model fine tuning 1:49

pretty helpful!

Thank you very much for your work!

very helpful video and easy way to explain the content. thanks alot

Anomaly detection is unsupervised, how did you get to if a point is anomaly or not, even before training the model ?

Very clear in very short VDO!!!!

Thanks for this valuable work. Helps me learning the subject.

Really great content! Learnt a lot. Thanks for your hard work!

This is an incredibly helpful video. One thing I noticed is that all features are numerical. How do we approach feature selection with a mix of numerical and categorical features? Also, when we have categorical features, do we first convert them to numerical features or first do feature selection. A video on this would be really helpful. Thank you

Hi Marco! I'm working on a project and this has a lot of components I need. I noticed the specification of the data said that it was being recorded every 5 minutes, could you create a tutorial on how to retrieve a stream of live data and pass it to the algorithm in a somewhat real-time fashion? I hope this is similar to what I understood from your data collection in the video

Great explanation. Easy hands-on as well!!

Hey !, Is it possible to identify and flag anomalies within a continuous numerical attribute?

Should we use the pc scores as the input for k-means or the original dataset?

hey Marco!! This is the first time I've watched one of your videos, and after 5 minutes of starting the video, I quickly went through your entire channel, looking at your content. It's AMAZING! Thank you for all your efforts to share your knowledge with the community. A hug from Chile!!

Excellent presentation. Very clear explanation. Would be great to have more info on the impact of the context and wich one of the methods is expected to work best in wich context.

What is the accuracy?

Can you teach how to do MRMR feature selection in ML?