AI — TensorFlow
What is TensorFlow?
Open-source machine learning framework by Google.
Install
pip install tensorflow
Basic Model
import tensorflow as tf
# Create model
model = tf.keras.Sequential([
tf.keras.layers.Dense(128, activation='relu'),
tf.keras.layers.Dense(10, activation='softmax')
])
# Compile
model.compile(optimizer='adam',
loss='sparse_categorical_crossentropy',
metrics=['accuracy'])
# Train
model.fit(X_train, y_train, epochs=10)
Layers
| Layer | Description |
|---|---|
| Dense | Fully connected |
| Conv2D | Convolutional |
| LSTM | Recurrent |
| Dropout | Regularization |
Mini Practice
- Install TensorFlow
- Build simple model
- Train and evaluate
- Try different layers
Up Next
Continue with PyTorch — PyTorch basics.
Related Topics
Frequently Asked Questions about TensorFlow
What is TensorFlow in AI?
TensorFlow is a fundamental concept in AI. This lesson explains it step by step with clear examples, making it easy for beginners to understand.
How do I learn TensorFlow?
Start by reading the explanation above, then try the code examples. Practice by modifying the examples and experimenting with different values. Hands-on practice is the best way to learn TensorFlow.
Why is TensorFlow important in AI?
TensorFlow is essential for AI development. Understanding this concept will help you write better code and solve real-world problems more effectively.