Data science in Python: pandas, seaborn, scikit-learn

In this video, we'll cover the data science pipeline from data ingestion (with pandas) to data visualization (with seaborn) to machine learning (with scikit-learn). We'll learn how to train and interpret a linear regression model, and then compare three possible evaluation metrics for regression problems. Finally, we'll apply the train/test split procedure to decide which features to include in our model.

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[Emmaizam]

This is the best ML tutorials I have ever seen! Thank you very much Sir.

[TheBurningofSolomon]

MANY THANKS!!!

All other data science tutorials (for beginners) go by way to quickly. Some people may find you going slowly a nuisance, but I found it to be EXTREMELY HELPFUL. THANK YOU! Subbed ^__^

[prachinainawa]

I'm a beginner but your way of teaching makes me love machine learning, I feel it's so easy. Even you make me understand how the algo is working behind the scene. Love from India...

[TheGautamj]

The csv file does not load up. Has the url changed?

[pratikdhumal]

I was searching for appropriate videos on ML from long time. After following this series i can say that it is the best which i have ever seen.Each and every concept is covered with great detail. Same applies for study material and links. Thanks Data School

[kennyl]

wonderful videos! I would like you to focus on scikit-learn, and your style of teaching which combines hands-on with scikit-learnt, real examples, explanation of ML techniques are very helpful!

[siddhidhavale]

Hi, the file URL isn' valid. Can you please share it?

[JackSimpsonJBS]

Thank-you so much for your explanations of sk-learn, it finally makes sense to me! I'm already pretty familiar with Pandas so I'd love to learn more about sk-learn, because I feel there are so many other machine learning algorithms I'd love to get my head around.

[brothermanbill]

when I use seaborn to pairplot the data, it doesn't show data for first column i.e. 'TV'

[lakswin]

Kinda complete one, putting together all at-once! The best, I have watched until now!

[gangele]

Can you please start teaching us deep learning and neural network?

[jan]

Your video is really good ! Do you have the video of preprocessing?? I want to learn about
this technique

[ankitbiradar]

Could you teach how to program Neural Networks and SVM using sckit-learn ?

[musabosman]

Nicely presented and delivered. Thank you!. I have subscribed to your channel!

[your_buddy_]

Thank you very much
Your teaching methodology is awesome making things crystal clear.

[Superdooperhero]

I watch way too much training videos and I would like to say that I wish you were the presenter in all of them. You rule at this training thing!

[LekanMakanju]

This is unreal! I literally abandoned my datacamp machine learning course for this one and no regret at all. I especially like that you taught the underlying mathematical concept of how these codes come to be. You also speak clear and understandable English plus the sound system is top notch. I've taken your Data science course and your and prof Allen's remains my best to date with Hugo's coming in a distant 3rd. And to think you recorded this more than 7 years ago makes you conclude that this is way ahead of its time

[shivbalaji]

You are doing a great job Thank you very much for all your valuable videos !!! They are really helping me !!!! Thanks again :-)

[subratkumarsahoo]

Guys if any one is getting error on this line :
sns.pairplot(data, x_vars=['TV', 'radio', 'newspaper'], y_vars='sales' )
you need to mention the exact same column names in x_var and y_var attributes.

[tissues]

You're a way better instructor than my college professors. The syntax is fairly simple and the explanation of the statistical intuition behind the metrics made this enjoyable.