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Techniques
Last updated on April 11, 20241 min read

Techniques

Dive into the 'Techniques' section and unravel the intricate processes powering AI's magic. From the nuances of data preparation to the prowess of transformers, journey through the stages that bring AI to life.

Artificial intelligence is anchored by a vast array of techniques that define its functionality and capabilities.

Model Development:

Dive into the stages of AI model progression:

  • Data Handling: Grasp the intricacies of sourcing, cleaning, and preprocessing data—the foundation of any AI system.

  • Training & Validation: Understand the balance of model learning, the art of avoiding overfitting, and the pursuit of generality.

  • Deployment & Scaling: Discover how trained models are seamlessly integrated into real-world applications and scaled to handle vast datasets.

Architectural Explorations:

Venture into the blueprint of AI systems:

  • Classical Models: Revisit the foundational architectures that paved the way, from decision trees to support vector machines.

  • Neural Networks: Dive deep into the layers of perceptrons, convolutional networks, and recurrent models.

  • Transformative Designs: Encounter advanced structures like transformers, responsible for breakthroughs such as GPT and BERT.

For both budding AI enthusiasts and seasoned experts, the "Techniques" section serves as a bridge to the underlying processes and methods that make AI the formidable force it is today.

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