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Convolutional Neural Networks for Medical Images Diagnosis
Quick Facts
| particular | details | |||
|---|---|---|---|---|
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Medium of instructions
English
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Mode of learning
Self study
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Mode of Delivery
Video and Text Based
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Course and certificate fees
Fees information
₹ 449 ₹1,799
certificate availability
Yes
certificate providing authority
Udemy
The syllabus
Introduction
Getting and Preparing Data
CNN Architecture
- Overview of CNN Architecture
- CNN Convolutional Layer
- CNN ReLU Activation
- CNN Max-pooling Layer
- CNN Flattening Layer
- CNN Fully Connected Layer
- CNN Softmax Classifier
CNN Training
- Data Normalization
- Cross Entropy Loss function
- CNN Backpropagation
- Python Implementation of CNN Training
CNN Evaluation
- Performance Measures
- ROC Curve
- Python Implementation of CNN Evaluations
CNN Improvement
- CNN Hyper-Parameters Tuning
- Analyse the effect of pooling layer.
- Using Different Optimizers
- Data Augmentation
- Using Dropout Regularization
- Batch Normalization
- Leaky ReLU Activation
- Early Stopping
CNN Transfer Learning
- Transfer Learning using Oxford VGG Network
- Transfer learning with shallow VGG network
- Transfer Learning using Microsoft ResNet Network
- Transfer Learning using Google Inception Network
CNN Visualization
- CNN Layers Visualization
CNN Deployment
- CNN Model Deployment
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