With all the hype around AI, I decided to pause CS50 and learn some AI.
First, I tried AI for Everyone on Coursera. Here’s the first week.
Week 1:
- AI consists of:
- ANI – Artificial Narrow Intelligence
- AGI – Artificial General Intelligence
- Machine Learning
- Supervised Learning -> Basically and input to output mapping using AI to get the output.
- Neural Net -> Way of adding huge performance into AI system for large data increases
- What is Data? –> Basically, just tables!
- Supervised Learning -> Basically and input to output mapping using AI to get the output.
- AI Terminology
- Machine Learning – Output is often software that computers use to learn things without being explicitly programmed
- Data Science – Output is often a slide deck. Science of extracting knowledge from data.
- Deep Learning – Use a neural network to get an output from an input. Used interchangeably with the phrase ‘neural network’. A neural network is really just a big maths equation! Deep learning is a subset of machine learning.
- For a neural network – you can feed the software lots of data with the inputs and the corresponding outputs. The software can then figure out what the actual network should be and do.
