Live-Discussing All Hyperparameter Tuning Techniques Data Science Machine Learning 

A TRUE LEGEND AND MASTER OF DATA SCIENCE!!!! THANK YOU KRISH NAIK!!! YOU'RE A REAL GEM FOR THE WORLD OF DATA SCIENCE!!!!! GOD BLESS YOU MAN! ✌️💖

Explained so well. My confidence in DS increases day by day through your videos. 😊

1:05 question from watchers : "why multiplication?". The result of embarking on this path without learning the necessary mathematics.... So it's a simple probability case. God help them in situations that require more advanced math.

I love ur clarity on the subject . Best teacher in the youtube

Let me tell u you are the gem of the game out of all the ones teaching data science on RU-vid passing us real world thought process of a datascientist working in a real world scenarios Love from Karachi Pakistan,🇵🇰

great work, very clear and helpful for my project that I am working on. Thanks a lot!

Thanks again Krish Naik amazing efforts and commitment so grateful.

please do a video on FasterRCNN and Yolo object detection

BEST VIDEO EVER .....HATS OF TO YOU SIR 🙏

Sir please make a video on yolo object detection 🙏

if possible.. please do video on faster rcnn and yolo object detection without github repo.. or even with github repo.

Damn!!! I couldn't thank you enough for this ever.. 🙏🏻🙏🏻

Krish really amazing knowledge sharing ..gr8 work..

Shouldn't we split our data before imputing any sort of values to prevent data leakage?

Thankyou so much sir for this detailed explanation ❤️

U just covered all the stuff in one cool video, this just blew my mind bro. I just cant say one reason for not subscribing your channel. Thank you very much...! 💕

Thank you sir 🌟

Hi Krishna I have seen your most of the video

Thanks for sharing the knowledge.

finished watching

Hello sir, I am from Bangladesh and always watch your video. Can you make some videos about fusion models.

THANK YOU BRO IT WAS AMAZING SESSION

9:30 GridSearchCV and RandomizedSearchCV are good

first time I ma seeing you in funny mood, good to see you like this else aap to bhagwan shanker ki tere gusse mein hi dikhte hain.

Starts at 11:30

I have tried hyper parameter and my laptop take 6 hrs to give the parameter what should I do ! It is wasting my time.

Sir Please makes video on Mathematics behind on SVM Regression, AdaBoost Regression, Gradient Boost Classification

Yes

yes

WHEN WILL OBJECT DETECTION GOING LIVE ??

thank you sir...why dont i get accuracy value..? so there is no return value on loss

But using tpot can I print the values of the hyper parameter for which our model has best accuracy...

can i implement these concept if i have continuous value as output ie if I want to do regression problem

Grid search will be best I guess

How to reduce the false positive and false negative

Best session please conduct such kind of class

hey question how do you get the predictive text?

Telegram link is not opening

how u r not getting error while u having 1 as int value in min_samples_split which is not allowed ! although i m getting this error (min_samples_split must be an integer greater than 1 or a float in (0.0, 1.0]; got the integer 1) which is right : we can either use 1.0 float or greater value than int 1

Krish you are amazing, keep it up! One comment, I wouldn't take too high values ​​for the 'max_depth' parameter because of overfitting issues...

hi good evening

can we do stratifiedkfold validation in gridsearchcv or randomsearchcv

Good evening sir, I needed some guidance how can I can contact with you?

HIi Krish I got this error how to solved it. ValueError: Invalid parameter min_sample_split for estimator RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None, criterion='gini', max_depth=None, max_features='auto', max_leaf_nodes=None, max_samples=None, min_impurity_decrease=0.0, min_impurity_split=None, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, n_estimators=250, n_jobs=None, oob_score=False, random_state=None, verbose=0, warm_start=False). Check the list of available parameters with `estimator.get_params().keys()`.

I got an error :cant pickle file and send it to workers when i ran the randomsearch cv

7:33

finished coding

When you are pissed off of copy pasting things - 46:52

Yed

the lecture is good but shaking legs does not seem good kris.

Hello everyone, I get an error regarding accessing subscript for the randomizedsearchcv object, 1 from sklearn.model_selection import GridSearchCV 2 param_grid = { ----> 3 'criterion': [rf_randomcv['criterion']], 4 'max_depth': [rf_randomcv['max_depth']], 5 'max_features': [rf_randomcv['max_features']], TypeError: 'RandomizedSearchCV' object is not subscriptable

Thank you so much sir 😊😊

Yes