How do you decide weather the data is large or not ?

@@veeresh4441 by number of records and features....ultimately size of data

@@reenasheoran893 suppose you have some 10000 rows and 100 columns or features , do u consider this big?

@@veeresh4441 no

Perfect 🤞🏻😎😎

we should not say trial and error.. but we can say we have model evaluation techniques like the confusion matrix, classification report to determine which model is performing better in that particular data set. its always better to check with 5, 6 models before coming to a conclusion about the data set. I guess you were correct the only thing was not to mention trial and errr thing :)

Search in google

Yes, they helps in finding best hyper parameters available in your parameter space. But again it depends upon your parameter space, how you are choosing that.

You can use pair plot, in short visualize the data first and then you will get to know whether it is linearly separable or not

Auto ML models does that for you. It applies every ML algorithm (a bit consuming, though not much) and gives u the result.

That depends on the algorithm..if it's linear regression, it uses least squares to determine the line of fit. It will calculate values that minimize the square of residuals from tht line. If it's logistic regression, it follows max likelihood estimation..if it's decision trees, the algorithm follows entropy or gini index and node impurity to calculate the best split and goes until the depth you define. So each algorithm has its own set of criteria and methods to follow.. these are some of the ones that I know. Correct me if I'm wrong.

@@pravali4452 you said that is correct but that is not answer to my question

When error value(loss) doesn't change much after each training iteration? Is it right? If not, may I know what's the answer!

Crash course in Python is a good book to start.

Better to check python documentation... best way to learn python

Model needs to be created in that way

@@krishnaik06 I thought your first approach "after performing EDA, selection of model" was the best one.

Yes but now if see the automl models they verify with all the algorithms

@@krishnaik06 Yaa right. Microsoft Azure does the same thing.

@@shanbhag003 Why should one worry about choosing right algorithm when we have AutoML!!

:) I really adore him

@@krishnaik06 That's wonderful and we adore you ...please do your traditional kindo videos which you used to do at the beginning....thank you 👍

Don't think no one can be compared with Srikanth sir..he is in different league

@@vyshagha3747 There's no comparison which im making....we are already standing on the shoulders of Gaints. Its my observation which I expressed.