Polynomial Regression w Luis Serrano & YouTube's Video recommender Algorithm | Machine Learning # 8

📚About
This lecture introduces Polynomial Regression with @SerranoAcademy. Youtube's Recommendation Algorithm utilizes polynomial regression as means to predict a users watchtime for future videos.

⏲Outline⏲
00:21 Theory & Examples with @SerranoAcademy
03:36 YouTube's Video Recommendation Algorithm
09:24 Polynomial Regression on sklearn
18:27 Higher Degrees ?
23:11 Overfitting vs Underfitting
24:34 Learning Curves
35:52 Outro

Grokking Machine Learning

Luis Serrano Adademy

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Instructor: Dr. Ahmad Bazzi

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Credits:

Google

Google Photos

TensorFlow

scikit-learn

Numpy

Microsoft OneNote

Python

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References:
[1] Géron, Aurélien. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems. O'Reilly Media, 2019.

[2] Bishop, Christopher M. Pattern recognition and machine learning. springer, 2006.

[3] Friedman, Jerome, Trevor Hastie, and Robert Tibshirani. The elements of statistical learning. Vol. 1. No. 10. New York: Springer series in statistics, 2001.

[4] Burkov, Andriy. The hundred-page machine learning book. Quebec City, Can.: Andriy Burkov, 2019.

[5] Goodfellow, Ian, Yoshua Bengio, and Aaron Courville. Deep learning. MIT press, 2016.

[6] Chollet, Francois. Deep Learning mit Python und Keras: Das Praxis-Handbuch vom Entwickler der Keras-Bibliothek. MITP-Verlags GmbH & Co. KG, 2018.

[7] De Prado, Marcos Lopez. Advances in financial machine learning. John Wiley & Sons, 2018.

[8] Duda, Richard O., Peter E. Hart, and David G. Stork. Pattern classification. John Wiley & Sons, 2012.

[9] Lapan, Maxim. Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more. Packt Publishing Ltd, 2018.

[10] Bonaccorso, Giuseppe. Machine Learning Algorithms: Popular algorithms for data science and machine learning. Packt Publishing Ltd, 2018.

[11] Deisenroth, Marc Peter, A. Aldo Faisal, and Cheng Soon Ong. Mathematics for machine learning. Cambridge University Press, 2020.

[12] Krollner, Bjoern, Bruce J. Vanstone, and Gavin R. Finnie. "Financial time series forecasting with machine learning techniques: a survey." ESANN. 2010.

#MachineLearning #TensorFlow #MachineLearningTutorial

[SerranoAcademy]

Thanks for having me in your channel, Ahmad! And hello to all of Ahmad's fans over here!

[bang]

When combining two scientists in one video, this is what you get. You’ve got an ML expert over here guys, i.e. Prof. Luis Serrano, whose PHD involved a lot of Schubert analysis. Dr. Ahmad Bazzi is a signal processing expert and is the inventor of the JADED algorithm, that is JADED-RIP: Joint Angle and Delay Estimator and Detector via Rotational Invariance Properties. Excellent combo. Keep up the good work guys. I feel blessed to have subscribed to both channels. Thank you for spreading your knowledge.

[skayaan]

I do a lot of ML research and I find this to be simply brilliant. I clicked on the video from reddit since I saw Luis Serrano, who I know is a guru. Keep up the noble work guys.

[d.a.sfourteen]

Ahmad Bazzi teams up with Luis Serrano to get this. I never knew that YouTube has a recommendation algorithm based on machine learning. Thank you Luis for the clear explanation.

[hnktwlr]

Wow Luis Serrano is here. Luis Serrano is a machine learning mogul, I've subscribed to his channel and followed his content especially the ones on natural language processing.

[cabeceourbano]

When Luis Serrano is on a video, you should know it's full of information.

[furkancicek]

Thank you very much Luis Serrano and Ahmad Bazzi. You guys are the best.

[khawaraltaf]

Ahmad Bazzi is one of the best youtubers in terms of machine learning and convex optimization

[hikemusicworld]

Amazing explanation supported by super meaningful visuals.

[oyunvakti]

Thanks! I usually use R, but have a project started in Python.

[bar]

Was watching a video on how to get my YouTube video recommended, and I got this.

[husenpro]

Thank you very much for the code. Helps a lot to follow.

[aligok]

I'm impressed by the animations and the python implementation.

[trapwolves]

That's one tough lecture. Damn. Lots of information should have made a series.

[fantasticmix]

Amazing lecture on Polynomial regression. Please do another on on ridge regression I have pretty much a tough time on understanding the loading parameter lambda.

[bhairoislive]

You both make me feel like my bachelors in engineering went all for a waste, economically. Thanks a lot but no thanks. LOL.

[nilmson]

Is there also nonlinear regression ? For example, a model involving nonlinear function such as logs and exponentials ? Thank you in advance.

[saiteja-gjmk]

Great video but I have a question does models overfit if we add higher dimensions.

[vladymyrmelnyk]

Still don't see any reason why I should use polynomial regression instead of NN of linear functions. As far as I am aware the NN of simple linear activation functions can approximate even better than polynomial regression.

[funnyjumping]

This is not public. Ahmad, I’m trying to share this on Facebook but I can not get your thumbnail to show, could you please make the lecture public. 
Thumbs up, up up.