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CNN – Convolutional Neural Networks.
Convolutional Neural Networks Syllabus: 1. Fundamentals of CNNs What are CNNs? Differences between CNNs and fully connected networks. Applications of CNNs. Components of CNNs Convolution layers. Filters (Kernels) and their role. Stride, Padding, and their effects. Activation Functions ReLU, Sigmoid, Tanh, etc. Pooling Layers Max pooling, Average pooling, Global pooling. Fully Connected Layers How they integrate features learned from convolutional layers. 2. Advanced Architectures and Concepts Popular CNN Architectures LeNet, AlexNet, VGG, ResNet, Inception, MobileNet, EfficientNet. Residual Networks (ResNets) Skip connections and their significance. Inception Networks Factorized convolutions and mixed architecture. Depthwise Separable Convolutions Efficiency in MobileNet and EfficientNet. Dilated
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For A Batch Of 100 Records How The Records Will Be Passed At A Time Or One By One?
For A Batch Of 100 Records How The Records Will Be Passed At A Time Or One By One? Answer: For a batch of 100 records in a neural network, all 100 records are passed through the network at the same time (in parallel), not one by one. This is made possible through vectorized operations and the efficient handling of data by modern hardware like GPUs. Why Are Records Processed Simultaneously? How It Works Internally: Summary: How Individual Neurons Operation Happens: Yes, the operations we discussed (matrix multiplication, bias addition, and activation) apply to individual neurons as part of the
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When Does The Weights Of The Neural Networks Are Updated?
When Does The Neural Network Is Updated? Answer: The weights in a neural network are typically updated after each batch during training, not after each epoch. This depends on the type of gradient descent being used. Types of Gradient Descent and Weight Updates:
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What Is An Epoch ?
What Is An Epoch? (1) What Is An Epoch? An epoch in deep learning refers to one complete pass through the entire training dataset by the neural network during training. It is a key concept when training machine learning models, especially neural networks, to understand how data is processed and how the model learns. (2) Key Points About Epochs: (3) Examples Of Epochs (4) Why Are Multiple Epochs Needed? (5) Choosing the Right Number of Epochs (6) Visualization
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What Is Albumentations Python Library?
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What Is Token ID and Attention Mask In NLP?
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What Is Temperature Hyperparameter?
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What Is Number Of Workers In Deep Learning?
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What Is Batch Size In Deep Learning?
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What Is Patience In Deep Learning?
