Neurale netwerke (NN)
Neurale netwerke is een van die belangrikste ontdekkings in die geskiedenis.
Neurale netwerke kan probleme oplos wat nie deur algoritmes opgelos kan word nie:
- Mediese Diagnose
- Gesigopsporing
- Stemherkenning
Neurale netwerke is die essensie van Deep Learning .
Die Deep Learning Revolution
Die diep leer revolusie is hier!
Die diepleerrevolusie het omstreeks 2010 begin. Sedertdien het Deep Learning baie "onoplosbare" probleme opgelos.
Die diep leer-revolusie is nie deur 'n enkele ontdekking begin nie. Dit het min of meer gebeur toe verskeie nodige faktore gereed was:
- Rekenaars was vinnig genoeg
- Rekenaarberging was groot genoeg
- Beter opleidingsmetodes is uitgevind
- Beter stemmetodes is uitgevind
Neurone
Wetenskaplikes stem saam dat ons brein ongeveer 100 miljard neurone het.
Hierdie neurone het honderde biljoene verbindings tussen hulle.
Beeldkrediet: Universiteit van Basel, Biozentrum.
Neurons (aka Nerve Cells) are the fundamental units of our brain and nervous system.
The neurons are responsible for receiving input from the external world, for sending output (commands to our muscles), and for transforming the electrical signals in between.
Neural Networks
Artificial Neural Networks are normally called Neural Networks (NN).
Neural networks are in fact multi-layer Perceptrons.
The perceptron defines the first step into multi-layered neural networks.
The Neural Network Model
Input data (Yellow) are processed against a hidden layer (Blue) and modified against another hidden layer (Green) to produce the final output (Red).
Neural Networks with JavaScript
Artificial Intelligence can be math-heavy. The nature of neural networks is highly technical, and the jargon that goes along with it tends to scare people away.
This is were JavaScript can come to help. We need easy to understand software APIs to simplifying the process of creating and training neural networks.
JavaScript Libraries
Brain.js
Brain.js is a JavaScript library that makes it easy to understand Neural Networks because it hides the complexity of the mathematics.
Building a neural network with Brain.js.
Introduction to ml5.js
ml5.js is trying to make machine learning more accessible to a wider audience.
The ml5 team is working to wrap machine learning functionality in friendlier ways.
The example below uses only three lines of code to classify an image:
<img id="image" src="pic1.jpg" width="100%">
<script>
const classifier = ml5.imageClassifier('MobileNet');
classifier.classify(document.getElementById("image"), gotResult);
function gotResult(error, results) { ... }
</script>
Try substitute "pic1.jpg" with "pic2.jpg" and "pic3.jpg".
TensorFlow Playground
TensorFlow Playground is a web application written in d3.js.
With TensorFlow Playground you can learn about Neural Networks (NN) without math.
In your own Web Browser you can create a Neural Network and see the result.
TensorFlow.js was previously called Tf.js and Deeplearn.js.
Tom Mitchell
Tom Michael Mitchell (born 1951) is an American computer scientist and University Professor at the Carnegie Mellon University (CMU).
He is a former Chair of the Machine Learning Department at CMU.
E: Experience (the number of times).
T: The Task (driving a car).
P: The Performance (good or bad).
Stories
Giraffe
In 2015, Matthew Lai, a student at Imperial College in London created a neural network called Giraffe.
Giraffe could be trained in 72 hours to play chess at the same level as an international master.
Computers playing chess are not new, but the way this program was created was new.
Smart chess playing programs take years to build, while Giraffe was built in 72 hours with a neural network.