GridSearchCV | Hyperparameter Tuning | Machine Learning with Scikit-Learn Python

In this Scikit-Learn learn tutorial I've talked about hyperparameter tuning with grid search. You'll be able to find the optimal set of hyperparameters for any machine learning model using this method!
#machinelearning #python #scikitlearn

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[krimsonsun]

DUDE!!! You are the Guru among common minds. This was the best explanation ever. Simple succinct and easily understandable for a newbie like me. I also like you give extra homework, and nuggets of knowledge related to the topic that I can look into afterwards. Now time to study the rest of your videos 👍⭐⭐⭐⭐⭐

[philipbutler]

I learned about grid search for a course last semester, it was for a final project on sklearn that I waited to start 3 days before it was due, so I rushed to learn a lot of concepts that I promised myself I’d go back and understand more thoroughly (and probably will need to for upcoming courses/career). So this was an awesome refresher on this topic! Love your videos, keep up the great work!

[shwetabhat]

Hope you are doing well sir . Kindly continue your video series as it greatly helps and is just amazing!! 🙂

[mikeboudhabhay]

thanks for your work and dedication . your vid is very useful for my final project in DS bootcamp.

[yusufpradanaajisurya]

Thank you!! This is the best video on this subject!

[cvrbcheppali]

Very nice and one of the best video on Hyperparameter Tuning

[ramblingsofadegenerate]

Recently found your channel very grateful

[raselsheikh]

This is my first comment at youtube. I came here because of your video quality and realize your explanation also fanstastic. I think you are using manim. For me it's a great chanel.

[shoaibsh]

I knew about grid search, but in the end the technique you shared was new to me and it will be really helpful in the future when I'm going to use grid search, thank you for sharing. Great vid as always 😊

[tomliao]

thanks for sharing especially for the last part that how to choose an efficient model with low computer resource wasting haha

[samikshakolhe]

Awesome Explaination! appreciate your work and subscribed;)

[fosheimdet]

From now on, I identify as a person from the future😊

[bassamdaou]

Thank you. Please can you make a video explaining how we can make prediction from different regression models: regression tree, random forest, artificial neural network, SVM, Bagged CART, Generalized boosting, Extreme Gradient boosting

[KayYesYouTuber]

Thanks. Nice video. But why are you doing GS.fit (X_train, Y_train) when you already have cross validation with cv = 5. Shouldn't you just do GS.fit (X, Y) ?

[grumpy_techo]

I have just stumbled upon you channel. you videos are well communicated. Well done. Another good video could be - how do you settle on a model that is generalised to test data.

[humblebrag]

Why do we need to split it to be X_train and y_train when internally in gridsearchCV we will conduct k-fold? please help me answering this question.

[jessemutiga]

there'll alway be a random indian out there who will help you get your assignment done on time.

[amirhosseinrahimi]

Thanks, one queation, after tuining the model and finding the best hyper parameter, is it necessary to run the model with found best parameter for moel training right and prediction? i mean after using GridSearchCV, model is already configured by best parameter? can you please elaborate?

[chongzhang]

What about the the testing data? It seems u have not used them.

[MessiasBatista]

Hello, congratulations for video.

I have a question. You have a example that discovers the best hyper-parameters using Swarm Intelligence?