Kaggle's 30 Days Of ML (Day-9): First Machine Learning Model and Validation

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This video is a walkthrough of Kaggle's #30DaysOfML. In this video, we will build out first #MachineLearning model and will also look into model validation!

Note: this video is not sponsored by #Kaggle!

Please subscribe and like the video to help me keep motivated to make awesome videos like this one. :)

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A tutorial like this should be provided by Kaggle, makes it much easier to understand.

isaacyn

This is great, your video provides extra info n knowledge on top of the course itself, thank you!

cjj

Abhishek, thanks for the video! The Kaggle lessons were really brief and I didn't realize how much I was missing out until I saw your videos.

TajminurRahmanmeshadowscream

Great video specially the part explaining the classes of problems models address, this is very useful I think for sm1 approaching and learning ML #30DaysOfML. Though have gone through all these before but these videos are a very good refresher .

GauravRawat

Thank you Sir, these daily videos are extremely helpful. I really appreciate your efforts and helps newbies like me a lot and not to get lost or left behind.

trojan

29:47
This isn't the way we calculate mean absolute error ?
def mea(y_true, predictions):
y_true = np.array(y_true)
predictions = np.array(predictions)

mea =
return mea

Schadenfreude

At 13:15 you talk about it being a regression problem and the various kind of problems it has, could you point towards how to understand these? Are there any parameters on which you choose different kinds of models which are better to predict the outcome?

snehangsude

Is there any reason not to reindex the data frame after dropping NaN values?

augustasmacijauskas

I want to get all of your .ipynb file related to this tutorial. Thanks

bipulasarcomilla

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