The Semicolon
#EnsembleLearning #EnsembleModels #MachineLearning #DataAnalytics #DataScience
Ensemble Learning is using multiple learning algorithms at a time, to obtain predictions with an aim to have better predictions than the individual models.
Ensemble learning is a very popular method to improve the accuracy of a machine learning model.
It avoid overfitting and gives us a much better model.
bootstrap aggregating (Bagging) and boosting are popular ensemble methods.
In the next tutorial we will implement some ensemble models in scikit learn.
For all Ipython notebooks, used in this series : https://github.com/shreyans29/thesemicolon
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can u make video on interview questions with explanation please
i'm waiting for interview questions video and aswell please make video on Tensorflow and how to launch and use tensorboard.
i stuck in using tensorboard graphs and how to make use of it in nlp. thank u so much for efforts.
Excellent !! Explained in a very easy way.
bro can you give me some information like document/video about ensemble learning as I have to create a report for that
Thanks in advance.. 🙂
Excellent Description in a very simple way… Thanks a ton!!
thanks. people like you make the world a better place
This was good video. Could you please make a video on how to implement stacking of 2 to 3 algorithms in R or Python? I would highly appreciate it. Please.
Really it's wonderfull (y)
Clearly explained, please keep going!
Best way to pitch the learning
i think sample size of each bag should be same as train data i.e. size-N….where N= test data…size=complete data….train data=size-N……….and u mentioned size-M<N…
really cool thanks a lot! it will great if you could show some exemples with knime
Thanks for sharing knowledge . Explained concepts clear and simple.
what do you mean by "combine it with the previously trained model to form an ensemble" at 5:35. Combining of models ? How ?
Hey buddy you have made a great video…. Subscribe and like +1
Legend leve explanation
So young and so talented.Appretiated
thanks dude
great explanation 🙂
Nice and crisp explanation…
compact and clean explanation
wonderful explanation….
The explanation on bagging is the best I have ever seen.
Much better explained :), great job keep going.
outstanding video,clearly explained !Thanks
Awesome job explaining this! Thank you.
Good job explaining boosting!
Can't express how satisfying it was to watch the hand writing. Lol. Thanks. You are much better than my professor!
thank you very much for sharing
God bless you
Very good Explanaton! Awsome
Amazing and clear. Just didn’t quite get the boosting party but I’m still a beginner haha
Wow amazing explanation .this is very clean and practical ..keep it up … thanks for uploading
You have explained the concept in very easy way.
Thanks a lot.
Small query: In Bagging do we take data into the bags with replacement or not?
Great explanation
Hey Shreyans! Awesome Detailed Explanation. Can we please have a link to slides in the video so that in case of revision we can go through this quickly?