🤖

adam

🤖

sgd

Which should you use?

Adam adapts learning rates per parameter and includes momentum, while SGD is simpler but may need careful tuning.

Key Differences

Factor

adam

sgd

Learning Rate

Adaptive per parameter

Single global rate

Momentum

Built-in (first + second moment)

Optional add-on

Tuning

Less tuning needed

More tuning for best results

Generalization

Sometimes worse

Often better with tuning

Use adam when:

Quick convergence needed

Less hyperparameter tuning time

Sparse gradients (NLP)

Default choice for beginners

Learn adam

Use sgd when:

Maximum generalization performance

Time for learning rate scheduling

Computer vision tasks

Research comparing to baselines

Learn sgd

Ready to learn both algorithms?

Interactive lessons with visualizations and hands-on practice

Explore ML Algorithms

🤖

adam

🤖

sgd

Which should you use?

Adam adapts learning rates per parameter and includes momentum, while SGD is simpler but may need careful tuning.

Key Differences

Factor

adam

sgd

Learning Rate

Adaptive per parameter

Single global rate

Momentum

Built-in (first + second moment)

Optional add-on

Tuning

Less tuning needed

More tuning for best results

Generalization

Sometimes worse

Often better with tuning

Use adam when:

Quick convergence needed

Less hyperparameter tuning time

Sparse gradients (NLP)

Default choice for beginners

Learn adam

Use sgd when:

Maximum generalization performance

Time for learning rate scheduling

Computer vision tasks

Research comparing to baselines

Learn sgd

Ready to learn both algorithms?

Interactive lessons with visualizations and hands-on practice

Explore ML Algorithms