en/resources/deep-learning/introduction

🧠 Introduction to Deep Learning

Deep learning is a subset of machine learning that focuses on algorithms inspired by the structure and function of the brain, called neural networks. These networks learn to perform tasks by considering examples, generally without being explicitly programmed for the task.

Key Concepts

• Neural Networks: Composed of layers (input, hidden, output) that process data hierarchically.
• Training Process: Adjusts weights through backpropagation and optimization algorithms like SGD or Adam.
• Applications: From image recognition 📷 to natural language processing 💬, deep learning powers modern AI.

Learning Resources

• 📘 Deep Learning Overview – Explore foundational theories and architectures.
• 🎓 Hands-On Tutorials – Practical guides for beginners.
• 📚 Books & Papers – Recommended readings for advanced learners.

For visualizing neural network structures, check out this interactive diagram. Dive deeper into specific topics like CNNs or RNNs for targeted learning!