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Machine Learning Specialization
Welcome
Emily Fox & Carlos Guestrin
Machine Learning Specialization
University of Washington
1
©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
Machine learning is
changing the world
2
©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
Old view of ML
Data
3
ML
Algorithm
My curve
is better
than your
curve
Write a
paper
©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
4
©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
Search
Retail
Movie
Distribution
Coupons
Disruptive companies
diļ¬€erentiated by
Networking
INTELLIGENT
APPLICATIONS
Music
Advertising
Campaigning
using
Real Estate
Machine Learning
Human
Resources
Legal
Advice
Dating
Wearables
CRM
5 Taxis
©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
The machine learning pipeline
Data
6 ML
Method
Intelligence
©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
ML case studies
7
©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
Case Study 1:
Predicting house prices
ML
Regression
Method
$
$
$
+ house
features
8 Intelligence
$ = ??
price ($)
Data
house size
©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
Case Study 2:
Sentiment analysis
ML
Classification
Method
Data
Sushi was awesome,
the food was awesome,
but the service was awful.
Score(x) < 0
“awful”
All reviews:
Intelligence
Score(x) > 0
“awesome”
9 ©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
Case Study 3:
Document retrieval
Data
ML
Clustering
Method
SPORTS
10 ENTERTAINMENT
Intelligence
WORLD NEWS
SCIENCE
©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
Case Study 4:
Product recommendation
ML
Method
Your past
purchases:
+ purchase
histories of
all
customers
11 Intelligence
Recommended
items:
Customers
Data
Products
©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
Case Study 4:
Product recommendation
Data
Your past
purchases:
ML
Matrix
Method
Factorization
Customers
features
Intelligence
Recommended
items:
features
features
+ purchase
histories of
all
customers
12 Products
features
features
features
©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
Case Study 5:
Visual product recommender
ML
Deep
Method
Learning
Data
Input images:
13 Intelligence
Layer 1
Layer 2
1
1
x1
z1
x2
z
Nearest neighbors:
y
2
©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
A unique ML specialization
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©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
Not like other ML
courses out there…
From use cases to
models & algorithms
15 ©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
First course is about building, evaluating
and deploying intelligence in each case study…
Data
Task
16 ML
Method
Model &
parameters
Intelligence
Optimization
algorithm
Evaluation
Use pre-specified
(black box)
©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
Subsequent courses provide depth in
models & algorithms, but still use case studies
2.
3.
4.
5.
Regression
Classification
Clustering & Retrieval
Matrix Factorization &
Dimensionality Reduction
6. Capstone: Build an
Intelligent Application
with Deep Learning
17 ©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
2. Regression
Case study: Predicting house prices
Models
• Linear regression
• Regularization:
Ridge (L2), Lasso (L1)
Algorithms
• Gradient descent
• Coordinate descent
Concepts
18 • Loss functions, bias-variance
tradeoļ¬€, cross-validation, sparsity,
overfitting, model selection
©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
3. Classification
Case study: Analyzing sentiment
Models
Algorithms
Concepts
19 • Linear classifiers
(logistic regression, SVMs, perceptron)
• Kernels
• Decision trees
• Stochastic gradient descent
• Boosting
• Decision boundaries, MLE, ensemble
methods, random forests, CART,
online learning
©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
4. Clustering & Retrieval
Case study: Finding documents
Models
• Nearest neighbors
• Clustering, mixtures of Gaussians
• Latent Dirichlet allocation (LDA)
Algorithms
• KD-trees, locality-sensitive hashing (LSH)
• K-means
• Expectation-maximization (EM)
Concepts
• Distance metrics, approximation
algorithms, hashing, sampling algorithms,
scaling up with map-reduce
20 ©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
5. Matrix Factorization & Dimensionality Reduction
Case study: Recommending Products
Models
• Collaborative filtering
• Matrix factorization
• PCA
Algorithms
• Coordinate descent
• Eigen decomposition
• SVD
Concepts
21 • Matrix completion, eigenvalues,
random projections, cold-start
problem, diversity, scaling up
©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
6. Capstone:
An intelligent application using deep learning
Build & deploy
a recommender using
product images and
text sentiment
22 ©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
This specialization is for you if…
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©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
Level of the specialization
Motto:
tough concepts made intuitive
and applicable
minimize prereq knowledge
maximize ability to develop and deploy
learn concepts through case studies
24 ©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
Target audience
Software engineer
Scientist
Data enthusiast
25 ©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
Math background
• Basic calculus
- Concept of derivatives
• Basic linear algebra
- Vectors
- Matrices
- Matrix multiply
26 ©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
Programming experience
• Basic Python used
- Can pick up along the way if
knowledge of other language
27 ©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
Computing needs
• Basic desktop or laptop
• Access to internet
• Ability to:
- Install and run Python
- Store a few GB of data
28 ©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
You’ll be able to do
amazing things…
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©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
Our journey together…
Course 1:
build intelligent
applications
30 Courses 2-5:
formulate,
implement &
evaluate
ML methods
Course 6:
design & deploy
an exciting
application
©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
The Capstone Project:
Build and deploy an intelligent
application with deep learning
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©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
An intelligent recommender
using images & text
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©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
We will do something even more exciting…
Text
sentiment
analysis
Computer
vision
Capstone
project
Deep
learning
Recommenders
Deploy
intelligent
web app
33 ©2015 Emily Fox & Carlos Guestrin
Machine Learning Specialization
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