Here's what you'll hear when you first get into machine learning.
- Neural networks
- Loss
- Weights
- Biases
- Epochs
- Neurons
- Optimizers
...
It can get very confusing really fast!
Here are some of the terms you should know about.
(I wish I had this before)
🧵👇
These terms won't mean anything unless you know what Machine learning is all about.
> Machine learning is the process of making a program which allows a computer to learn from data.
The data could be anything, images, audio or even text.
In machine learning we use something called a neural network, this is essentially an imitation of the human brain.
> Neural Networks are a digital imitation of the neurons you see in the human brain.
In these neural networks, data flows through them and each neuron (the circle) has a numerical value which will change.
> The value of a neuron gets changes to something which is close to what we want each time the data passes through the neural network.
Think of the neurons as dials on a lock, you have to tune every dial to open the lock.
It is almost impossible for a human to tune thousands of dials like these, but a computer certainly can.