At 18:43 , don't we have a dataleak ? for example we use index values 1 to 10 to predict value 11. After we use the value 11 to predict the value 12. So we used a futur value to predict the value 12 and not the predicted value 11, so the model corrects itself ? Or is it not the cas and we use predicted values as input values to predict the next futur values (in that cas it is not a data leak) ?
In the MLP network, data from independent variables from date t are used to predict a future value t+n. In the LSTM network, instead of using only data from time t of the independent variables, it uses data from time t, t-1, t-2, ..., t-n as desired by the programmer, and after that, generates the prediction for a future time t+n? Is this reasoning correct? Thank you very much!
Hi! Excelent video! How you can apply the model with new data, i mean when you have new variables without the temperature values. You would like to predict the new (future) temperature values? I hope you can help me with this. Thanks!
Nice Explanation about the multivariable input LSTM. I have an enquiry if given multiple numbers rows including target variable (or every feature has multiple values) at a particular time (t1). Then how to handle these cases in sequences and labels
It looks like the prediction is worse than a simple model that says "the temperature tomorrow will be the same as the temperature today". In both cases, when there is a sudden temperature change, there is a one day lag between the actual and predicted temp. In other words, it is not really much of a prediction! Or have I missed something?
nice bro can you show us how to forecast or predict weather using LSTM and CNN( Hybrid model) and show us important points to consider in order to successfully achieve the project.
@@geodev Where is the code that shows the target value of the temperature variable?, I tried to change the actual values from true_temp to true fog, the graph results are still the same. Thank you
Hi, I am sorry, I already deleted the best model weight. But definitely you can train this model in Google Colab since it doesn't take much time to train the model.
the only video that makes me understand this concept; thanks for sharing :)
You're very welcome!
Finally understood multivariate Time series in LSTM. Thanks. Very nice and informative video 👏
Glad it was helpful!
thank you brother, you're a god amongst men
At 18:43 , don't we have a dataleak ? for example we use index values 1 to 10 to predict value 11.
After we use the value 11 to predict the value 12. So we used a futur value to predict the value 12 and not the predicted value 11, so the model corrects itself ? Or is it not the cas and we use predicted values as input values to predict the next futur values (in that cas it is not a data leak) ?
Thanks! Very good video 💯
Glad it was helpful!
Thank you for sharing this good piece of materials with us dai
You are welcome vai❤️
Welldone Tek 👏
Thank you 🙌
In the MLP network, data from independent variables from date t are used to predict a future value t+n. In the LSTM network, instead of using only data from time t of the independent variables, it uses data from time t, t-1, t-2, ..., t-n as desired by the programmer, and after that, generates the prediction for a future time t+n? Is this reasoning correct? Thank you very much!
Yes, that's correct.
Can I use the R2 value to measure the accuracy of the LSTM model in time series prediction?
Hi! Excelent video! How you can apply the model with new data, i mean when you have new variables without the temperature values. You would like to predict the new (future) temperature values? I hope you can help me with this. Thanks!
Nice Explanation about the multivariable input LSTM. I have an enquiry if given multiple numbers rows including target variable (or every feature has multiple values) at a particular time (t1). Then how to handle these cases in sequences and labels
It looks like the prediction is worse than a simple model that says "the temperature tomorrow will be the same as the temperature today". In both cases, when there is a sudden temperature change, there is a one day lag between the actual and predicted temp. In other words, it is not really much of a prediction! Or have I missed something?
you can predict further into the future than one day
amazing.
nice bro can you show us how to forecast or predict weather using LSTM and CNN( Hybrid model) and show us important points to consider in order to successfully achieve the project.
Good work
Thank you! Cheers!
love thiss tysm!!
So glad!
Can you share any code/video for multivariate and multistep forecast using LSTM?
what tools are very important for weather forecasting ?
I have problem when creating sequence showing keyError. How to slove it?
Without the full error log, I can't say anything. Also, from which line are you getting the error?
Hello teacher! Do you have in mind to record a video teaching how to make forecast about drought using Google Earth Engine?
Why don't you select the parameters? I have 15 parameters and I need to select the most important ones. How can I do this?
How can I control forecast time in future ?
Using the previous days forcast, you can predict future.
ao you have 9 features included temperature. and the target feature is temperature ?
Yes that's correct. The idea of lstm weather prediction is, based on the historical weather pattern, we can predict the current or future weather
@@geodev Where is the code that shows the target value of the temperature variable?, I tried to change the actual values from true_temp to true fog, the graph results are still the same. Thank you
Can anyone say, where is best weight function
Could u tell me what is the best Library for deep learning to learn
Tensorflow and pytorch are the most popular libraries in Python.
@@geodev could u plz make a video about ML project from extract values in arc pro till end
Hello...
Can I have private chat with you on LSTM and CNN... Am comparing the two in predicting Cassava yield
can you provide the best model weight?
by the very helpful video❤
Hi, I am sorry, I already deleted the best model weight. But definitely you can train this model in Google Colab since it doesn't take much time to train the model.
Dai aba ML and Data Science for Atmospheric Remote Sensing ...ma mentoring garnu peryo :D
It is on my list vai, stay tuned! For now, I am creating content related to data preparation and image segmentation!
Could you send the code
You can get the code in the video description!
Quá hay
I am very grateful for this comprehensive explanation. I have some questions. Could you please get your email?
You can get my email in my channel description.