Building the Neural Network — Chapter Summary
ICSE · Class 12 · Artificial Intelligence
Summary of Building the Neural Network for ICSE Class 12 Artificial Intelligence. Part of the ICSE Class 12 Artificial Intelligence syllabus.
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Overview
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, primarily developed by the Google Brain Team. A neural network in Keras follows a standard five-step workflow: prepare
Key Concepts
Keras is a high
Keras is a high-level neural network API in Python that simplifies constructing and training neural networks. It is used for image, video, text, audio
TensorFlow is an open
TensorFlow is an open-source, end-to-end machine learning platform. Its name comes from tensors flowing through a graph of operations.
The Sequential model represents a linear
The Sequential model represents a linear stack of layers and is the easiest way to define a model architecture.
A Dense layer is a fully
A Dense layer is a fully connected layer where every neuron is connected to every neuron in the previous layer. It performs the heavy lifting of learn
The Flatten layer transforms a 28x28
The Flatten layer transforms a 28x28 image into a 1D vector of 784 numbers. Neural networks generally need 1D vectors as input.
Learning Objectives
- Use Keras and TensorFlow to build a neural network
- Train a neural network using the fit() function
- Understand the five-step Keras workflow
- Identify the role of layers such as Dense, Flatten, and Dropout
- Choose suitable activation functions, loss functions, and optimizers
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Sources & Official References
Content is aligned to the official syllabus. Refer to the board website for the latest curriculum.
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