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Tagged with optimization

3 cards

React Hard Theory

React performance: slow apps, unnecessary re-renders, React.memo, PureComponent, code splitting, lazy loading, Suspense, virtualization, profiling, and bundle size

React apps become slow when they re-render too much, do expensive work in render, or ship more code and DOM than needed.

Measure before optimizing
Code splitting and virtualization reduce big costs
Memoization helps only when it prevents meaningful work

#optimization #performance #react

React performance: slow apps, unnecessary re-renders, React.memo, PureComponent, code splitting, lazy loading, Suspense, virtualization, profiling, and bundle size

Machine Learning Easy Theory

What is a learning rate?

The learning rate controls how large each parameter update step is during training.

Too high can overshoot
Too low learns slowly
Often tuned experimentally

#ml #optimization #training

What is a learning rate?

Machine Learning Medium Theory

What is gradient descent?

Gradient descent updates model parameters in the direction that reduces the loss function.

Uses gradients of loss
Step size is learning rate
Variants include batch and mini-batch

#ml #optimization #training

What is gradient descent?