// The Library
Technical Deep Dives,
& systems logic.
Consult the index...
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3. Computer Vision: Transfer Learning
A small guide on how transfer learning using pre-trained models.
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2. Computer Vision: Pre trained Models
A small guide on how to work with pre-trained models.
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1. Computer Vision: Architecture
A description on working of CNNs.
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6. Neural Nets: Regularization and Normalization
Regularization Techniques.
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5. Neural Nets: Implementing MLP using PyTorch
Implementing Multi Layer Perceptron
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4. Neural Nets: Loss and Optmization
Dicussion about different types of Optimization functions and losses
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3. Neural Nets: Activation Functions
Overview of differnet types of Actiavation functions.
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2. Neural Nets: Preprocessing data
Brief description on how data can be processed.
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1. Neural Nets: Overview
Overview of Neural Networks
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