feat: Add implementation of Adaptive Neural Complexity (ANC) algorithm

[MuhammadBabarWaseem]

Summary

This Pull Request introduces the Adaptive Neural Complexity (ANC) algorithm, a novel approach to dynamically adjusting the architecture of neural networks based on input data complexity. The algorithm also integrates meta-learning techniques to self-tune hyperparameters during training.

Key Features:

• Dynamic Neural Architecture: Automatically adds or prunes layers depending on the complexity of the data.
• Meta-Learning Hyperparameter Tuning: A meta-controller adjusts learning rate, dropout, and other hyperparameters in real-time.
• Efficient Learning: Balances resource usage by maintaining optimal network size for the given task.

Files Added:

• adaptive_neural_complexity.py: Contains the full implementation of the ANC algorithm.
• README.md: Explains the algorithm, its usage, and contributions for Hacktoberfest 2024.

This PR is part of Hacktoberfest 2024 and aims to push innovations in adaptive AI, ML, and DL methods.

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