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machine-learning

Basics of neural network architecture

3 roles need it, 1 as coreUsually level 2: BasicsLesson available

Where it sits

Learn first

Introduction to neural networks

This skill

Basics of neural network architecture

Leads to

BackpropagationIntroduction to Deep Learning

Jobs that need it

What level 2 (Basics) means

Can use it with guidance. Level 3 (Working): uses it independently on the job.

Start learning

✨Towards Deep Neural Networks in NumPY

A Beginner's Guide to Deep Learning

16 parts

Open the lesson

Find out where you stand

A free check, then a route that starts at your level.

Check my readiness

Learned alongside it

A composite function and its derivativeAccuracy and confusion matrixActivation functionsAgglomerative clusteringAI EngineerBackpropagationBasic data typesBayes theorem

Basics of neural network architecture: common questions

What is Basics of neural network architecture?

Basics of neural network architecture is a skill in machine-learning, needed by 3 roles on BootSelf.

Which jobs need Basics of neural network architecture?

Data Scientist, AI Engineer, MLOps Engineer. Most ask for level 2 (Basics): can use it with guidance.

What should I learn before Basics of neural network architecture?

Introduction to neural networks.

How do I practise Basics of neural network architecture?

Check your readiness for free, then BootSelf builds a route and short daily learning loops: a little theory, checks on what you get wrong, then a small program.