Linear Regression And Residuals - Pandas For Machine Learning 28

In this video we'll finnish creating our Linear Regression Model using the Diabetes Dataset from SciKit-Learn.
We'll Create our Linear Regression, then fit the data to our model and make our predictions.
Then we'll get R2 Scores, Mean Squared Errors, Mean Absolute Erros, and the Intercept.
Finally we'll create a scatter plot of the Regression as well as the Residuals.
#pandas #codemy #JohnElder
Timecodes
0:00​​ - Introduction
0:56 - Create Linear Regression Instance
1:44 - Train The Model
3:50 - Make Predictions From Testing Set
5:45 - Get R2 Score, MSE, MAE, and Intercept
8:28 - Explaining The Metrics
11:58 - Graph The Scatterplot
15:15 - Graph The Residuals
17:34 - Conclusion

[@Codemycom]

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[@carolmcsween-brooks3089]

This is INCREDIBLE!!! I've been reading so many Python tutorials on this and gotten nowhere in understanding. These 3 videos made sense of over 25 hours of reading tutorials. Thank you. I have subscribed and bought the lifetime membership. You rock!!

[@hgjghjkhify]

I watched videos 27 and 28 in this series to see how training/testing works together with linear regression. My online program sometimes requires us to learn certain concepts on our own, so I'm grateful for these. You explained everything clearly, and I was able to apply this to my own computer performance dataset, which is not as pretty, but now I know why! 😀

[@Codemycom]

Happy to hear it!

[@ChanceMinus]

Excellent series! I was able to brush up on my knowledge of Pandas and Linear Regression. Thank you for providing such helpful content.

[@Codemycom]

Glad you enjoyed it!

[@sushibooshi]

this is taught so well! You should really do more machine learning videos

[@Codemycom]

Just started a new Machine Learning Monday playlist yesterday.

[@ErenMC_]

@@Codemycom will you teach it in python too? I see you have started with R

[@TkinterPython]

@@ErenMC_ of course

[@patricklandia1]

Thanks for your videoo!!, is great, Greetings from Uruguay!

[@Codemycom]

welcome!

[@patricklandia1]

it coming more content for models? , kind regrestion, classification and more ? Greetings !@@Codemycom

[@ErenMC_]

13:38 Why have we used y.min,y.max here and why have you written it two times?

[@CharlesIhara]

Hi, thanks for the great tutorial! I was a little confused by your explanation of the intercept_ for LinearRegression at 11:18. How does the sign of the intercept tell you whether the target increases or decreases as the features increase? Wouldn't this information be discerned from the sign of the slope rather than the intercept?

[@ErenMC_]

I have a question, the only way to make the model more accurate is to make the data for training more?

[@ringogold]

👍

[@Codemycom]

:-)

[@aenugulasheikdadapeer5336]

Sir please do more videos on machine learning algorithms

[@Codemycom]

We'll see :-) I'm doing a deep learning with pytorch playlist at the moment.

[@aj5686]

Thank you for detailed tutorial👏. I have a doubt, How can we increase our accuracy from 45 to some higher value? Let's say 60-70%.. How can we do that? If possible please make a video on it. Thank you.

[@Codemycom]

You don't. The data is what the data is. If you run an experiment and get a certain outcome...that's the outcome. You don't change the experiment to get an outcome that you like more...

[@mariabelencuadros6199]

Sir, would you like to teach at LFC ? My professor kinda dumb...

[@Codemycom]

Ha

[@skillpolice5348]

Who are here after completing the entire series 🙋‍♂

[@Codemycom]

🙋‍♂