Open TarunTomar122 opened 4 years ago
I would love to work on this part.
@quadri-haider-ali Sure go ahead. Issue assigned to you.
I would also like to work on this issue
@SaiSrichandra You can work on this... Do Tell prior what loss function are you going to add?
I will add the KL Divergence loss
Okay @SaiSrichandra do keep us updated
Hey I would like to add mean squared logarithmic error(msle) and root mean squared logarithmic error(rmlse).
@parva-jain sure go ahead. Keep us updated on your progress and feel free to ask anything in the Gitter channel for further clarification.
Hey @rohansingh9001 I would like to add root mean squared logarithmic error (rmsle)
Hey @rohansingh9001 I would like to add root mean squared logarithmic error (rmsle)
Actually, I'm ready with the loss function of mean squared logarithmic error and derivative equation of mean squared logarithmic error(handly written) and only left with its implementation in python. Also @rohansingh9001, the equation is a bit complex so how should I justify it?
Hey I would like to add the Triplet loss. Refer this for more info. on it.
I would like to add cosine similarity loss function.
@Vinit-source and @Udit-git-acc, Okay 👍
I would like to add logcosh_loss function
@Siddharth-Singh27 sure, go on
Completion Phase-1
Huber Loss -> Shreya Sachan Cosine Similarity -> Udit Agarwal Mean Squared log loss -> Devyani Gorkar Log cosh loss -> Siddharth Singh
I would like to add the Binary Crossentropy loss function
Sure, go ahead
I want to add hinge function loss , Will I ?
Sure, Go ahead :) Just check in the files, whether hinge function loss is already there or not?
I would like to add the Poisson Loss function.
Sure, Go ahead :) Just check in the files, whether Poisson function loss is already there or not?
Right we have implemented only Mean Squared Error and Logarithmic Error as our loss functions in our module. As we are going to implement more and more machine learning algorithms we will need more loss functions. There in this issue you can add one or more loss functions like cross-entropy etc.
Resources:-
https://keras.io/api/losses/ <--------(Most of the known loss functions)
https://machinelearningmastery.com/how-to-choose-loss-functions-when-training-deep-learning-neural-networks/ https://heartbeat.fritz.ai/5-regression-loss-functions-all-machine-learners-should-know-4fb140e9d4b0 https://www.analyticsvidhya.com/blog/2019/08/detailed-guide-7-loss-functions-machine-learning-python-code/