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About All Projects F21
Here are some helpful deep learning concepts and techniques: - Neural Networks: The basic building block of deep learning. Multilayer perceptrons. - Convolutional Neural Networks: For image/visual data. Extract features automatically. - Recurrent Neural Networks: For sequential/time series data. Handle variable length sequences. - Long Short Term Memory Networks: Variant of RNNs to address vanishing gradient problem. - Transfer Learning: Use models pre-trained on large datasets to initialize your model. - Dropout: Regularization technique to prevent overfitting. Randomly drop units during training. - Activation Functions: Non-linearities like ReLU, sigmoid, tanh. Introduce non-linearity. -
Detailed Information
| Author: | ['Muzammil Khan'] |
|---|---|
| Publication Year: | 2022 |
| Pages: | 138 |
| Language: | English |
| Format: | |
| Price: | FREE |
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