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This lecture contains information about the definition, components, structure, and history of Neural Network
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A neural network is a computational model inspired by the way biological neural networks in the human brain work. It is used for various tasks such as pattern recognition, classification, regression, and decision-making. Neural networks consist of interconnected nodes or neurons organized in layers, and these networks are trained on data to learn patterns and make predictions.
(1. Input layer, 2. Hidden layers and 3.Output layers).
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A neural network is a computational model inspired by how biological neural networks work in the human brain. It is used in machine learning and artificial intelligence to solve various tasks, such as pattern recognition, classification, regression, and decision-making. Neural networks consist of interconnected nodes, or artificial neurons, organized into layers. The three main types of layers in a neural network are. 1. Input Layer: 2. Hidden Layers: 3. Output Layer:
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I learned in this lecture about the neural network ( functional unit of deep learning).
We will see how deep learning and neural networks are linked to each other.
First of all,
Deep Learning
is a subtype of
Machine Learning
and
Machine Learning
is a subtype of
AI
And
AI
is a subtype of
Algorithms.NEURAL NETWORK: A neural network is a series of algorithms that endeavor to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates.And I also learned about the components of neural network1- Neurons
2-Layers
(a)Input layer
(b)Hidden layer
(c)Output layer
3-Weights and Biases
4-Activation FunctionsALLAH PAK aap ko sahat o aafiyat wali lambi umar ata kray aor ap ko dono jahan ki bhalian naseeb farmaey aur aap ke walid-e-mohtram ko karwat karwat jannat ata farmaye,Ameen.
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