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

[@krimsonsun10]

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!

[@NormalizedNerd]

Thanks mate! It's always useful to revisit an old topic.

[@shwetabhat9981]

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

[@raselsheikh5800]

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.

[@NormalizedNerd]

Welcome to my channel! I'm really glad you that liked my content :D :D Yes, I use manim.

[@mikeboudhabhay6082]

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

[@yusufpradanaajisurya9176]

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

[@cvrbcheppali8214]

Very nice and one of the best video on Hyperparameter Tuning

[@shoaibsh2872]

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 😊

[@NormalizedNerd]

Yeah that's really helpful.

[@ZirothTech]

Great video, thanks again!

[@NormalizedNerd]

Glad you enjoyed it!

[@ramblingsofadegenerate1174]

Recently found your channel very grateful

[@harshavardhanm9481]

Nice, clean animations 👍

[@saurabhjoshi8776]

keep up the good work..😀

[@samikshakolhe5086]

Awesome Explaination! appreciate your work and subscribed;)

[@10955356]

amazing video my friend!

[@karlopoljancic]

Thanks! Gonna try this out!

[@lukehamilton8285]

great video helped me alot!

[@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.

[@collinspo]

Great content. Thanks

[@ganeshnaik6503]

This is awesome. Thanks!

[@PythonArms]

Great video. thank you

[@gouthamansaravanan7692]

Best one! Thanks!!

[@idrissjairi]

thank you so much for the great video

[@krepker]

Awesome video. tnx man!!

[@NormalizedNerd]

Thanks mate!

[@bassamdaou2908]

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

[@bzaruk]

Great vid! Thanks!

[@NormalizedNerd]

Thanks mate! :D

[@tomliao6667]

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

[@NormalizedNerd]

Glad it was helpful!

[@amirhosseinrahimi3964]

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?

[@MessiasBatista]

Hello, congratulations for video. I have a question. You have a example that discovers the best hyper-parameters using Swarm Intelligence?

[@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) ?

[@lukehamilton8285]

you should train on x_train and y_train because this allows you to further test the model once the optimal hyperparameters have been found with an unseen test set which the model has not seen stopping data-leakage

[@viniciuslazzeri3019]

Amazing! How can I implement this on fastercnns?

[@cyberpunk_edgerunners]

thanks ， my friend

[@tinanajafpour7214]

thank you for the video it was really helpful. I had a question, could you please help me? when I want to download data from kaggle, I receive 403 forbidden Error!

[@nachomacho7027]

Thank you bro

[@excursion5246]

thanks. Can you make a video about deep neural network regression predictions. Like multiple inputs and one output prediction by using this gridsearch. Thanks a lot.

[@antonellars22]

Thank you!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

[@fosheimdet]

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

[@jamalnuman]

great

[@chongzhang871]

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

[@Borschboy]

How does GridSearch work with pickeld data?

[@LeE-yr7lp]

Could you do a video about boosting models please? Thanks

[@Junistz]

Thanks for your video it is going to help me ! :D Invalid parameter "max_depth " contains whitespace. I got error kind of this ..

[@anurajms]

ty

[@deniskoala3131]

Thank you for this beautiful work. I have a question: what happens if we run the same code several times? Will the best_estimator always be the same? Thank you for your answer.

[@tomliao6667]

if you keep random_state the same number, I guess there will be the same best_estimator

[@kolboy2028]

which software do you use for your animation?

[@NormalizedNerd]

I used manim for intro animation

[@kolboy2028]

@@NormalizedNerd and for the rest of the video?

[@onestopzz6446]

Bro, even without hyper parameter tuning, I am getting more than 0.99 r2_score. But I am getting 0.96 r2_score with tuning. So how exactly this tuning is helpful?

[@achin_sharma]

it means default values are best fit for your dataset

[@736939]

Where are you? We miss you :(

[@jessemutiga6055]

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

[@NormalizedNerd]

lol...at least you are not outsourcing your assignments!

[@parulkhattar28]

1:53 -> 2D arrays not lists 😀

[@ikramed]

Random state why = 2021

[@rijwanapatel6942]

Hey buddy how old are your 😁

[@im4485]

Nice