Skip to content

This repo will contain detailed and more visualized tutorials on writing custom loss functions. Scope will be ranging from basic neural networks to RL

License

Notifications You must be signed in to change notification settings

ajithvcoder/Building_Custom_loss_functions

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 

Repository files navigation

Building_Custom_loss_functions

This repo will contain detailed and more visualized tutorials(loss and results) on writing custom loss functions. Scope will be ranging from basic neural networks to RL. it will also explain about existing loss function with SOTA results.

(We will have visuvalized graphs, explanation for why we used a particular loss function, explanations for why our custom loss function is working well. Also corresponding visuvalizable results will be shared.) Following will be covered:

Classification-

  • Normal CNN layers networks
  • Resnet, Densenet

Detection

  • Yolo
  • SSD, Mobilenet

Tracking

  • Deepsort+Yolo

Others

  • 4 GAN Models
  • 1 R-CNN model

RL - Single Agent

  • DQN Model
  • DDPG model
  • TD3 model

RL - Multi Agent

  • DQN Model
  • DDPG model
  • TD3 model

In case if above is finished we would proceed with building custom RL - Single agent and RL-Multi agent environments in next repo.

Completion of this would take a person from Beginer level DL programmer to intermediate level DL and RL programmer for sure.

Time lines:

Estimated start of project: After completeion of GANs repo

Estimated duration - 4 months to 5 months

About

This repo will contain detailed and more visualized tutorials on writing custom loss functions. Scope will be ranging from basic neural networks to RL

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published