This is Sudha Jamthe's lecture to the Masters program students of Barcelona Technology School. Covers Machine Learning introduction of technology foundation, use cases across multiple industries, jobs and varioys business roles to create Machine Intelligence Products and Services.

1. Machine Learning Introduction
for Digital Business Leaders
Sudha Jamthe
Barcelona Technology School,
Barcelona, Oct 2016
1IoTDisruptions.com http://bit.ly/IoTAIBook @sujamthe

2. Instructor: SUDHA JAMTHE
2
The IoT Show (YouTube)
Past : Mobile, Social Growth Leader
STEM & Regional Economic Development –
Turkey/Czech/Barcelona
CEO IoTDisruption, Technology Futurist
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3. MACHINE LEARNING IS A PART OF AI
3
Machine
Learning
VR
AR
Voice to Text
Text to Speech
Facial Recognition
Computer Vision
Natural Language Processing
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Copyright: Sudha Jamthe
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4. Machine Learning teaches computers
to develop programs with large
volume of data and drive decisions
without human intervention.
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5. What can a computer do with
Machine Learning?
1. Tell the self driving car to stop
2. This newsfeed is spam
3. This photo is the face of Sudha Jamthe
4. Sell this stock now
5. I recommend this movie on Netflix
6. I can confirm if this cell looks like cancer cell
or not
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6. My Machine Learning Dog
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7. Recommendation Engines
Amazon uses ML for video recommendation
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8. Facial Recognition – Google Photos
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9. Computer Vision
Take a series of 2D pictures to create a
3D analysis
e.g. Civilmaps, Robots, Wearable Pills
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10. Health Informatics
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Image: Stanford Student research on Cancer from Tobacco usage

11. Facebook – Spam Detection
• Facebook Spam Detection
• Credit Card company – Fraud Detection
• Pathogen in Blood Samples
11
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12. 12
WHICH ONE IS AMY MY ASSISTANT?
CLUE: Amy is a bot
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13. Language Translations
Live Demo (Try this on your
computers)http://www.ibm.com/watson/developerclo
ud/services-catalog.html
Speech to Text https://speech-to-text-
demo.mybluemix.net/
http://visual-recognition-demo.mybluemix.net/
https://cloud.google.com/products/machine-learning/
https://cloud.google.com/speech/
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14. GOOGLE DEEPMIND TO PREDICT KIDNEY
PROBLEMS (DEEP LEARNING ALGORITHM)
14
Image source: Digital Trends
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@sujamthe

15. AUTONOMOUS VEHICLES
15
Image: Scania
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16. 16
ROBOTS MAKING MACHINES
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17. Marketing
• Customer Segmentation
• Churn Prediction
• Customer Analytics
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18. Machine Learning APIs
• api.ai, Cogito, DataSift, iSpeech, Microsoft
Project Oxford, Mozscape, and OpenCalais.
• Amazon, Google, IBM Watson, and Microsoft
• Amazon AWS
serviceshttps://aws.amazon.com/machine-
learning/
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19. Machine Learning Jobs
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@sujamthe
19

20. Who Does Machine Learning Today?
• http://datam.i2r.a-
star.edu.sg/dad/dadMLlab.htm
• https://www.ml.cmu.edu/people/phd-
students.html
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@sujamthe
20

21. ML Job Roles in Companies Digital
Transformation
ML Researcher  ML Engineer -> Data
Scientist
ML Product Manager/Business Roles
(EVOLVING)
21
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22. Machine Learning Jobs (6.6K jobs)
• Facebook ML AI/ ML Program Manager
• Siemens - Senior Innovator – (Machine Learning / Deep Learning)
• Chief Machine Learning Scientist - $5m compensation package (FinTech)
• Twitter -Product Manager, Core Ads: Ad Supply Management
• SAP Frontend Developer for Machine Learning development
• GroupOn Director, Business Operations & Analytics
• Apple Sr. Infrastructure Engineer - Applied Machine Learning
• Machine Learning Deployment Engineer, Professional Services, Google Cloud
• Sr. Product Manager in LinkedIn, Splunk, Walmart, Cisco, Amazon
• Computational Biologist, 23andMe
• SAP, Director, Platform Strategy
• Visa, Senior Design Technologist
• CTO, XiQ
• Sr. Product Manager, Capital One Bank Labs
• Business and Market Strategist, Enlitic
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23. Machine Learning Jobs in Spain
• Business Transformation Manager Innovation ,
Zurich Insurance company
• Sr. Product Manager, Knowit
• Computer Vision & Machine Learning Jr,
Touchvie
• Human Machine Interaction Development
Lead, Telefonica
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24. How does Machine Learning Work?
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25. How does Machine Learning Work?
1. Supervised
– Get Training Data, Define factors, Remove biases
2. Unsupervised Learning aka Deep Mining
- No need to define factors, train same
architecture for generic problem solving.
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26. Machine Learning Works by Building
Data Models (a geometric shape of
data*)
image: Techemregence Gaussian mixture model
Training
Data &
Factors
Predict
Outcomes
to make
decisions
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27. Machine Learning Platform
(TensorFlow, ScikitLearn, Theano, Spark Mlib, H20)
The right model
(decision tree, nearest neighbor, neural net, support vector machine,
ensemble of multiple models)
A learning procedure to fit the data
(linear regression, gradient descent, genetic algorithms, bagging,
boosting, and other model-specific methods)
Right data and fit
(bias and variance, overfitting and underfitting, missing data,
data leakage)
Deploying a ML Service into a Product
(Identity, Data Governance, Algorithmic accuracy/
Compliance for industry)
Building Products with Machine Learning
© Sudha Jamthe
27IoTDisruptions.com http://bit.ly/IoTAIBook @sujamthe

28. Building Products with Machine Learning
28IoTDisruptions.com http://bit.ly/IoTAIBook @sujamthe
Pick a Machine Learning Platform
(TensorFlow, ScikitLearn, Theano, Spark Mlib, H20)
Develop the right stats model (decision tree, nearest neighbor, neural
net, support vector machine) and Fit the data using right learning
procedure ( linear regression, gradient descent, boosting, nagging)
Develop Training Data & Fit
(bias and variance, overfitting and underfitting, missing data,
data leakage)
Defining a ML Service into a Product
(Identity, Data Governance, Algorithmic accuracy/
Compliance for industry)
© Sudha Jamthe
ML Engineer
ML Researcher
ML Product
Manager

29. AI COMPANIES LANDSCAPE
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30. 30
INDUSTRIES IMPACTED BY MACHINE LEARNING
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31. Questions?
http://slideshare.com/sujamthe
Email me sujamthe@gmail.com
Twitter @sujamthe
IoT Disruptions 2020
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31
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