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7️⃣ **Cross Entropy Loss: Teaching AI to Learn Better** 🎯 | |
- AI makes mistakes, so we **measure how bad they are** using a **loss function**. | |
- Cross Entropy Loss helps AI **learn from its mistakes** and get better. | |
- Instead of guessing randomly, the AI **adjusts itself to improve its answers**. | |
8️⃣ **Backpropagation: AI Fixing Its Own Mistakes** 🔄 | |
- AI learns by **guessing, checking, and fixing mistakes**. | |
- It uses **backpropagation** to update itself, just like **learning from practice**. | |
- This helps AI **get smarter every time it trains**. | |
9️⃣ **Multi-Class Neural Networks: Picking the Best Answer** 🎨 | |
- AI doesn’t always choose between **just two things**; sometimes, it picks from **many choices**! | |
- It uses **Softmax** to figure out which answer is **most likely**. | |
- This helps in **image recognition, language processing, and more**! | |
🔟 **Activation Functions: Helping AI Think Faster** ⚡ | |
- AI uses **activation functions** to **decide which patterns matter**. | |
- Three important ones: | |
- **Sigmoid** → Helps with probabilities. | |
- **Tanh** → Balances data better. | |
- **ReLU** → Fastest and most useful! | |
- These make AI **learn faster and make better decisions**! | |