Building the Neural Network
ICSE · Class 12 · Artificial Intelligence
Complete topic list for Building the Neural Network in ICSE Class 12 Artificial Intelligence. Key concepts, sub-topics, and what to focus on for board exams.
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Topics in Building the Neural Network
Core Ideas of Keras and TensorFlow
- Keras is a high-level neural network API in Python that simplifies constructing and training neural networks.
- TensorFlow is an open-source, end-to-end platform for Machine Learning.
- TensorFlow is primarily developed by the Google Brain Team.
Five-Step Keras Workflow
- Creating a neural network in Keras involves a standard five-step workflow.
- Step 1 is Prepare Data: load the dataset and reshape or normalize it.
- Step 2 is Define Model: stack layers to create the architecture.
Layers and Model Building
- The Sequential model is a linear stack of layers and is the easiest way to define a model architecture.
- Dense layer is a fully connected layer where every neuron is connected to every neuron in the previous layer.
- Dense layer performs the heavy lifting of learning patterns.
Activation Functions, Loss Functions, and Optimizer
- ReLU introduces non-linearity and is used in hidden Dense layers.
- Sigmoid activation is used in the output layer for binary classification with a single unit.
- Softmax activation is standard for multi-class classification because it gives a probability distribution summing to 1.
Key Concepts
Central concept: Neural network construction and training using Keras and TensorFlow
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