Machine Learning Project in Python: Predicting California Housing Prices

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Thank you for watching the video! Here is the notebook: colab.research.google.com/dri...
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Опубликовано:

20 сен 2021

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Комментарии : 41

@GregHogg 11 месяцев назад

Take my courses at mlnow.ai/!

@michaelle1229 4 месяца назад

Thank you, Greg, for this amazing tutorial, helped me finish how to predict house prices in Melbourne.

@michaelle1229 4 месяца назад

I have a question, does neural networks can be helpful or useful to reduce any noise/interference or overfitting on the final dataset? If so, what conclusion do you make in this case?

@andreiardelean9324 Год назад

The video was very informative but I have what might be a silly question, however I am new to ML. How can we interpret the predicition values? I have seen you during the entire video mentioning here and there "oh this is overfitting" or "there is no overfitting here". I would like to know how can we differentiate overfitting by looking at the prediction values. Unless I am missing something?

@yanhu2011 10 месяцев назад

Amazing video! Do you currently have a video that talks different AI models ? Linear regression, neural networks etc? And when and why one should be used for a particular data set?

@agnesdemarco9386 4 месяца назад

You're the best! Brilliant and clear explanation!!!! Thank youuu!!!

@GregHogg 4 месяца назад

Very welcome 😁😁

@rednax25 Год назад

Please let us know how we can encourage you to do more videos like this......Thanks for the wonderful explanations. I really love your style of teaching.

@GregHogg Год назад

Thanks so much Alexander - which is my middle name by the way!

@denysshushpanov7630 Год назад

Great video! I have a question though, how would you approach data preprocessing while making predictions on trained model with the new data (let’s say user input or streaming)?

@GregHogg Год назад

As long as you have some predefined processing function that doesn't depend on anything, you would just apply that to every input

@arsheyajain7055 2 года назад

Great project!!

@GregHogg 2 года назад

Thank you ☺️

@MohdIrshad-hv4vw 2 года назад

That is good It will really helpful for me

@GregHogg 2 года назад

I'm very glad!

@ayamouallem3619 2 года назад

Great explanation !! but i have a question , how can i know the correct split for train , test and validation , is it ok if test and val cross in some data ??

@GregHogg 2 года назад

Roughly 70, 15, 15, at random

@user-up6wd6em5u Год назад

16:00 , i find a easy way to do: median_house_value = 'median_house_value' all_columns = list(data.columns) all_columns.remove(median_house_value) new_column_list = all_columns + [median_house_value] data_new = data[new_column_list] data_new

@user-up6wd6em5u Год назад

also 19:50 it can use another easy and auto way to split train_test from sklearn.model_selection import train_test_split X = data_new.drop(['median_house_value'], axis=1) y = data['median_house_value'] X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)

@sgpleasure 2 года назад

Thanks for the new video. Would using a PIPELINE be cleaner and recommended by you?

@GregHogg 2 года назад

You're welcome! Pipelines are great. I've never personally used them, but I know how they work and they're pretty awesome.

@mathhack8647 2 года назад

@39:00 the validate MSE is worse then the training. The model did not generalize but does this mean that's an overfitting issue.?

@GregHogg 2 года назад

Yes, we overfit to the training set :)

@anitube7360 2 года назад

can we have a project tutorial on real-time facial emotion detector in python......... plz tell the different approaches/methods that we can take to complete this project.

@GregHogg 2 года назад

Okay this will be added to the to-do list!

@thummapalasuresh292 2 года назад

Could you please provide the dataset....

@bnneit777 5 месяцев назад

Hi everyone! MSE and RMSE are too large, whether they are reasonable? All the predicting house price tasks I had done had the big MSE and RMSE like that.

@andrewsnell2309 2 года назад

I am doing this in google collab and and it keeps saying Import "tensorflow.keras..." could not be resol

@GregHogg 2 года назад

Are you importing exactly the same way?

@germanshepherd6638 4 месяца назад

Why didn't you show us how to create the API and upload it?

@longtruong9935 2 года назад

could you provide the notebook link?

@GregHogg 2 года назад

Thank you very much for reminding me - it's there now.

@mdashik2291 Год назад

Could u make a video for roadmap of machine learning & deep learning with Coursera in 2023 plz❤️

@GregHogg Год назад

I'd say my roadmap is still valid

@norbertishimwe228 5 месяцев назад

On 39:14 why did you predict on the train data instead of the test data?

@rohitsali2603 2 месяца назад

Because we have to calculate the mse of training data not testing data Because we want to know how much accurate our model is by learning from training data