Neural Networks: Beyond Basics
Delve deeper into neural networks, exploring advanced architectures and training techniques.
Learning Objectives
Enhance understanding of complex neural network architectures and training.
Topics
Convolutional Neural Networks (CNNs)
Explore the structure and function of CNNs.
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Recurrent Neural Networks (RNNs)
Learn about the architecture and applications of RNNs.
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Long Short-Term Memory (LSTM)
Understand the workings of LSTM networks.
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Optimization Techniques
Explore optimization techniques for neural networks.
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Regularization Methods
Learn various regularization methods to prevent overfitting.
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Transfer Learning
Understand the concept and application of transfer learning.
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Hyperparameter Tuning
Learn how to tune hyperparameters for optimal model performance.
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Case Study: Advanced Neural Networks
Analyze a case study focusing on advanced neural networks.
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Realtime audio conversation for interactive session.
Interactive realtime chat session.
Live whiteboard explanation and collaboration.
Real-time wide variety of examples.
Continuous assessment and feedback.
Progress monitoring and record progress journey.
Broadcast session with larger audience for free.
Attend audience queries and provide responses.