Thank you so much for your explanation :) This example shows how to use EfficientNet for image classification. But how can we use it for other tasks? for example we have a 1d signal (1000 samples) and we want to do a binary classification. How do we apply EfficientNet?
Please ma'am, I'm just going into learning EfficientNet, please how would you recommend going about that? I have little experience with python programming also. Thank you in advance.
You need a good understanding of Python programming. EfficientNet is a convolutional neural network (CNN), so you need to understand deep learning concepts like- Neural Networks: Perceptron, activation functions (ReLU, Sigmoid, etc.) Forward pass and backpropagation Optimization: Gradient descent, learning rates, and optimizers (Adam, SGD) Loss functions: Cross-entropy, mean squared error Convolutional Neural Networks (CNNs): Convolution layers, pooling, batch normalization, etc. Then learn EfficientNet.
Very good explanation! Only thing I'd have added is the speed difference between the models.
Good point!
Thank you so much for your explanation. ☺
You're welcome 😊
These are all awesome Thx!
Glad my videos are helpful
Thank you so much for your explanation :) This example shows how to use EfficientNet for image classification. But how can we use it for other tasks? for example we have a 1d signal (1000 samples) and we want to do a binary classification. How do we apply EfficientNet?
Tank so mach for your information you are very good.
You are welcome
Please ma'am, I'm just going into learning EfficientNet, please how would you recommend going about that? I have little experience with python programming also. Thank you in advance.
You need a good understanding of Python programming. EfficientNet is a convolutional neural network (CNN), so you need to understand deep learning concepts like- Neural Networks: Perceptron, activation functions (ReLU, Sigmoid, etc.)
Forward pass and backpropagation
Optimization: Gradient descent, learning rates, and optimizers (Adam, SGD)
Loss functions: Cross-entropy, mean squared error
Convolutional Neural Networks (CNNs): Convolution layers, pooling, batch normalization, etc.
Then learn EfficientNet.
that was really good but the question is
why did not you build it just like ResNet and Inception
Just trying different ways to use the models.
hi can u make a video explain about effiecient net lite?
Noted!
My jupyter is not importing efficient net what to do
Maybe because of the versions. Check how to import the efficientnet as per your tensorflow version.
thank you mom
Welcome!
thank you madam,
Welcome 😊
can you pin the paper link here please? thanks in advance.
arxiv.org/pdf/1905.11946.pdf