ShallowNeuralNetwork.md

1️⃣ Introduction to Neural Networks (One Hidden Layer) 🤖

• A neural network is like a thinking machine that makes decisions.
• It learns from data and gets better over time.
• We build a network with one hidden layer to help it think smarter.

2️⃣ More Neurons, Better Learning! 🧠

• If a network isn’t smart enough, we add more neurons!
• More neurons = better decision-making.
• We train the network to recognize patterns more accurately.

3️⃣ Neural Networks with Multiple Inputs 🔢

• Instead of just one piece of data, we give the network many inputs.
• This helps it understand more complex problems.
• Too many neurons = overfitting (too specific), too few = underfitting (too simple).

4️⃣ Multi-Class Neural Networks 🎨

• Instead of choosing between two options, the network can choose many!
• It learns to classify things into multiple groups, like recognizing different animals.
• The Softmax function helps it pick the best answer.

5️⃣ Backpropagation: Learning from Mistakes 🔄

• The network makes a guess, checks if it’s right, and fixes itself.
• It does this using backpropagation, which adjusts the neurons.
• This is how AI gets smarter with time!

6️⃣ Activation Functions: Helping AI Decide ⚡

• Activation functions control how neurons react.
• Three common types:
  • Sigmoid → Good for probabilities.
  • Tanh → Helps balance data.
  • ReLU → Fastest and most useful!
• These functions help the network learn efficiently.

📖 AI Terms and Definitions (Based on the Videos) 🤖

🧠 Neural Network

A computer brain that learns by adjusting numbers (weights) to make decisions.

🎯 Classification

Teaching AI to sort things into groups, like recognizing cats 🐱 and dogs 🐶 in pictures.

⚡ Activation Function

A rule that helps AI decide which information is important. Examples:

• Sigmoid → Soft decision-making.
• Tanh → Balances positive and negative values.
• ReLU → Fast and effective!

🔄 Backpropagation

AI’s way of fixing mistakes by looking at errors and adjusting itself.

📉 Loss Function

A score that tells AI how wrong it was, so it can improve.

🚀 Gradient Descent

A method that helps AI learn step by step by making small changes to improve.

🏗️ Hidden Layer

A middle part of a neural network that helps process complex information.

🌀 Softmax Function

Helps AI choose the best answer when there are multiple choices.

⚖️ Cross Entropy Loss

A way to measure how well AI is learning when making choices.

📊 Multi-Class Neural Networks

AI models that can choose from many options, not just two.

🏎️ Momentum

A trick that helps AI learn faster by keeping track of past updates.

🔍 Overfitting

When AI memorizes too much and struggles with new data.

😕 Underfitting

When AI doesn’t learn enough and makes bad predictions.

🎨 Convolutional Neural Network (CNN)

A special AI for understanding images, used in things like face recognition.

📦 Batch Processing

Instead of training on one piece of data at a time, AI looks at many pieces at once to learn faster.

🏗️ PyTorch

A tool that helps build and train neural networks easily.