🔮 Neural Networks
Neural Networks
The foundation of modern AI — networks that mimic neurons in the human brain
M+
Parameters
99%+
Accuracy
ms
Response Time
Key Features
What Makes This Technology Special
Neurons & Layers
Basic structure of Input, Hidden, and Output layers
Activation Functions
ReLU, Sigmoid, Softmax for non-linear decision making
Backpropagation
Weight adjustment algorithm to minimize error
Loss Functions
Measure error to improve model performance
Hyperparameter Tuning
Optimize Learning Rate, Batch Size, and Epochs
Regularization
Dropout, L1/L2 techniques to prevent overfitting
Benefits
Why You Need This Technology
Understand AI Foundations
Grasp the fundamental principles behind all Deep Learning
Multi-Modal Data
Process images, audio, text and numbers in a single model
Flexible Architecture
Design architectures tailored to specific problems
Easily Scalable
Scale model size based on accuracy requirements
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