How to evaluate ML models | Evaluation metrics for machine learning

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Information How to evaluate ML models | Evaluation metrics for machine learning

Title	:	How to evaluate ML models \| Evaluation metrics for machine learning
Lasting	:	10.05
Date of publication	:
Views	:	67 rb

I am working on regression evaluation I want to learn how to calculate MAS ,RMSE with example I aslo can not read the graphical representation of regression evaluation
Comment from : @KalsoomBano-h6x

super! thanks!
Comment from : @nikhilgoyal007

Well done 👍
Comment from : @inkurutimes

thanks a lot for your explanationsbr Seems the MSE is like Brier score?!
Comment from : @mahshidz6676

Interesting how most people jump to the RECALL section Why? Is it a harder topic?
Comment from : @EasyAIForAll

How about the differences here for a non-linear regression? :)
Comment from : @RollingcoleW

Thanks a lot I needed this clarification for my presentation
Comment from : @ahmadebrahem4611

great!
Comment from : @Lexxus28

Thank you so much, this video helped me understand the metrics in the clearest way possible
Comment from : @penelopeharo8591

"شكرا جزيلا لك"brThis means "thank you so much" in Arabic 🕴
Comment from : @sultanaaa8282

Thanks for this informative lecture
Comment from : @narendrapratapsinghparmar91

Please ma, can you share the codes you used to plot the true positive rate vs false positive rate graph, PR curve? It looks so beautify and i can't get the exact, please help Thanks in advance
Comment from : @jamesadeke9873

How to evaluate clustering algorithms like K-Means and Fuzzy C-Means
Comment from : @Mejhool-g5y

Greatt
Comment from : @haticeozbolat0371

This video helped me to pass the azure data scientist associate exam brThanks for the video
Comment from : @forprogramming8541

how to calculate the coefficient of determination (R2)
Comment from : @aymanekanaoui9604

Idk i somehow seem not being capable of following this pace
Comment from : @michaltrodler195

How do you pronounce "Accuracy"? Its so triggering lmaobrThats not american nor british english, right?
Comment from : @andresolbach

super clear explanation! I seldom leave comments, but this video totally amazed me!
Comment from : @louisawang1308

Well explained but might be good if you added something on threshold setting for binary classification
Comment from : @greenbrothersuk

Thank you for the informative video
Comment from : @daniocionini7043

bINSANELY/b helpful Thank you bso/b much!
Comment from : @xxelurraxx232

What do you think about repeated random data splitting eg you split the data 80 percent for train and 20 percent for test on a random basis that preserves the class structure vs k fold cross validation? Edit yep I now know this is worse
Comment from : @kristianfella-glanville

Good video thanks
Comment from : @kristianfella-glanville

Thank you for this video, Thank you so much I have questions to ask based on this model evaluation, my questions go like this sir, " is there a way to use the confusion matrix to know the exact datapoint in our dataset our model got wrongly during the predictive system? Also, Sir when we deploy our model to a web app using streamlit, can we use a confusion matrix to figure out which exact datapoint our model predicted wrongly by applying the confusion matrix to the final predictive system output in the web app ?
Comment from : @sholay7255

Wow, thank you so much for these video I am a software engineer by trade but increasingly big tech companies have ML system design as one of their interview rounds Your content was amazingly helpful in preparing for those interviews!
Comment from : @DiwasTimilsina