Hey @UTSAVS26 , I am Darsh Agrawal a fellow contributor and would like to contribute a stats_analysis folder.
The aim for this folder , after or during a project coders usually have display the analysis and statics of their project , this folder will hold such snippets of code which help user generate report fast like
Function to calculate inference speeds of their model
Functions to calculate common evaluation metrics such as accuracy, precision, recall, F1-score, and confusion matrix.
Function to calculate the size of the model in terms of memory usage, helping users understand the model's footprint.
Generate a summary of the model's parameters (number of layers, number of parameters, trainable vs non-trainable).
A function to plot the learning curve of training and validation accuracy/loss over time.
A function to plot the precision-recall curve, which is useful for imbalanced datasets.
and a lot more...
if you like my approach i would like to be assigned this task.
Hey @UTSAVS26 , I am Darsh Agrawal a fellow contributor and would like to contribute a stats_analysis folder. The aim for this folder , after or during a project coders usually have display the analysis and statics of their project , this folder will hold such snippets of code which help user generate report fast like
if you like my approach i would like to be assigned this task.