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Master Complex Architectures

Dive deep into transformers, GANs, reinforcement learning, and production systems. Build state-of-the-art models.

Prerequisites

  • Completed intermediate tutorials
  • Strong Python programming skills
  • Understanding of neural networks
  • Experience with PyTorch or TensorFlow
  • Linear algebra and calculus fundamentals
  • GPU access recommended
Review Intermediate Tutorials

Building a Recommendation System

Implement collaborative filtering and content-based recommendations at scale using matrix factorization and deep learning.

Collaborative FilteringMatrix FactorizationContent-Based+7 more
90 min10 lessons

Transformer Architecture Deep Dive

Understand attention mechanisms and build a transformer from scratch. The architecture behind GPT and BERT.

Self-AttentionMulti-Head AttentionPositional Encoding+9 more
120 min12 lessons

Deploying Models to Production

Learn best practices for serving ML models with high availability, low latency, and monitoring.

Model ServingREST APIsgRPC+5 more
75 min8 lessons

Generative Adversarial Networks

Build GANs for image generation, style transfer, and data augmentation. Understand generator-discriminator dynamics.

Generator NetworksDiscriminator NetworksTraining Dynamics+6 more
80 min9 lessons

Reinforcement Learning Fundamentals

Train agents with Q-learning, policy gradients, and actor-critic methods. Build game-playing AI.

Markov Decision ProcessesQ-LearningDeep Q-Networks+8 more
100 min11 lessons

Advanced NLP with Transformers

Fine-tune BERT, GPT, and T5 for specific tasks. Build chatbots, summarizers, and question-answering systems.

Fine-Tuning BERTGPT for GenerationT5 for Tasks+6 more
85 min9 lessons

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Master distributed training, MLOps, and cutting-edge research implementations.

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