Curriculum
Grade XII AI
Lessons
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Unit 1-Python Programming II
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Unit 2-Data Science Methodology (Capstone)
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Unit 3-Making Machines See
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Unit 4-AI with Orange Data Mining Tool
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Unit 5-Introduction to Big Data and Data Analytics
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Unit 6-Understanding Neural Networks
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Unit 7-Generative AI
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Unit 8-Data Storytelling
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Notes
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Unit 6-Understanding Neural Networks
School Revise · Class 12 Artificial Intelligence · Unit 6
Understanding Neural Networks
Code 843, Class 12. A neural network learns like a simple brain. Here we learn its parts and how it learns.
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What this unit is about
A neural network is a model loosely based on the brain. It is made of tiny units called neurons joined in layers, and it learns patterns from data.
1. Neurons and layers
A network has an input layer (the data), one or more hidden layers (that find patterns), and an output layer (the answer). Each link has a weight that decides its strength.
2. How it learns
The network makes a guess, checks the error (how wrong it was), and adjusts the weights to reduce the error. Doing this many times over the data is called training.
3. Why they are powerful
With enough data and training, neural networks can recognise images, understand speech and much more. Networks with many layers are called deep learning.
Practise with the interactive
Explore the idea by tapping. The interactive opens right here in the lesson.
Practice set A, multiple choice
1. A tiny unit in a neural network is a …
neuron.
2. The layer that receives the data is the …
input layer.
3. The strength of a link is its …
weight.
4. Networks with many layers are called …
deep learning.
Practice set B, short answer
1. What is a neural network?
A model made of neurons in layers that learns patterns from data.
2. Name the three kinds of layer.
Input, hidden and output layers.
3. How does a neural network learn?
It guesses, checks the error, and adjusts the weights, many times (training).
Quick summary
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A neural network is a model based loosely on the brain, made of neurons joined in layers: an input layer, hidden layers that find patterns, and an output layer. Each link has a weight. The network learns by guessing, checking the error, and adjusting the weights many times, called training. Networks with many layers are called deep learning. |
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These free Class 12 Artificial Intelligence (Code 843) notes explain understanding neural networks, neurons and layers, weights, how a network learns by training, and deep learning with clear examples and practice, for CBSE students across India and the Gulf including the UAE, Saudi Arabia, Qatar, Oman, Kuwait and Bahrain.
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