AI and machine learning
machine Learning lead is how AI learns
- Sentient robots
- Humans no longer being needed
- The rise of machines over mankind
artificial intelligence
- AI (kill all humans)
- Machine learning (this not AI)
- Deep learning (subset of Machine learning)
is this the End us all?? Absolutely!
This future can not be stopped, so let's just make the best of things now until they come for us.
WHY should
Machines learn things????
for Humans
We got Problems
They need decisions.
This can be hard.
"Given a decision where the logic is unknown to us, but we have observations about the decision process, it is possible to use statistical analyses of these observations to create an approximation of the decision logic." - Ryan Case
Big Problems
with Lots of data
we use this right now!!
What do machines learn about right now?
- Media - Netflix Movies
- Retail - Amazon Shopping
- Manufacturing - Output Lines
- Healthcare - Clinical similarity between patients
- Finance - Fraud Detection
Text
USE: Computer Vision
Netflix
USE: Thumbnails
Amazon
All the things... they do it so much they sell it because they sell everything
Locally
This is all happening in Eugene right now.
I KNOW
Working on Machine Learning in Eugene
Parts of MacHine learning
VOCABULARY mostly
Types of learniNg
Unsupervised learning
Learn the mapping of the data
Supervised learning
Data is mapped
Y = f(x)
Reinforced learning
Trial and ErroR with a feedback lOop
General ML Terms
DATA SET
A collection of examples
TRAINING
The process of determining the ideal parameters comprising a model
Model
THE REPRESENTATION OF WHAT A MACHINE LEARNING SYSTEM HAS LEARNED FROM THE TRAINING DATA
feature engineering
Creating PredictIon VARIABLES
Classification
labels for predictions
Loss
Loss is a number indicating how bad the model's prediction was on a single example. If the model's prediction is perfect, the loss is zero; otherwise, the loss is greater.
My first Experiment
What did I try??
Movie gross prediction based on a string containing genre and names attached to the film
Data Set Example
{"text":"Action Adventure Sci-Fi Bryan Singer Patrick Stewart Hugh Jackman Ian McKellen Famke Janssen","category":"150"}
157 million gross
Predict gross for: Action movie with Jackman and Singer??
const brain = require('brain.js');
const data = require('./movies.json');
const network = new brain.recurrent.LSTM();
const trainingData = data.map(item => ({
input: item.text,
output: item.category
}));
network.train(trainingData, {
iterations: 100
});
let movie = 'Action Bryan Singer Hugh Jackman');
const output = network.run(movie);
console.log('Category:' + output);My Brain.js Prediction = 100Million
X2: X-Men United (2003)
$110 Million
MY DATA WASN'T GREAT
I forgot movies can have 2 directors, no data on new actors, etc...
Take aways
AI and Machine Learning come with ethical questions
This technology is already everywhere
This is the future
Copy of learning Machine learning learning lunch
By Antonio Ortega
