SlideShare une entreprise Scribd logo
1  sur  26
Télécharger pour lire hors ligne
MACHINE LEARNING
A BEGINNERS GUIDE TO
A BEGINNERS GUIDE TO MACHINE LEARNING
INTRODUCTION: ANDREW RANGEL
▸ Background: Mobile Development
▸ Passion for new and exciting technologies
▸ Machine Learning (ML) for ~1 year
▸ Passion for education and teaching others
A BEGINNERS GUIDE TO MACHINE LEARNING
INTRODUCTION: MACHINE LEARNING
▸ What is it
▸ What is it for
▸ Who uses it
▸ Examples
▸ Tools to get started
▸ Misconceptions
A BEGINNERS GUIDE TO MACHINE LEARNING
INTRODUCTION: MACHINE LEARNING
▸ Scary!
▸ Math. Math. MATH!
▸ There are a set of basic elements
▸ Learning the mechanisms can elevate your career
A BEGINNERS GUIDE TO MACHINE LEARNING
WHAT IS IT
▸ Using algorithms to parse data and make a prediction
about the world
▸ Came from early (’56!) Artificial Intelligence minds
▸ An early use was Computer Vision
▸ ML / AI / CV / NN
▸ Training
▸ Not being told “what to do”
A BEGINNERS GUIDE TO MACHINE LEARNING
WHAT IS IT
▸ Linear Regression
A BEGINNERS GUIDE TO MACHINE LEARNING
WHAT IS IT
▸ Linear Regression
$12
A BEGINNERS GUIDE TO MACHINE LEARNING
WHAT IS IT
▸ Gradient Discent
A BEGINNERS GUIDE TO MACHINE LEARNING
WHAT IS IT FOR
AUDIO TEXT EVALUATE SCORE RESPOND
ERRORWEIGHTS
“Hey Siri what is the score of the Chiefs game?”
Chiefs
Game
Score
10
4
2
A BEGINNERS GUIDE TO MACHINE LEARNING
WHAT IS IT FOR
AUDIO TEXT EVALUATE SCORE RESPOND
ERRORWEIGHTS
“Hey Siri what is the score of the Chiefs game?”
Chiefs
Game
Score
10
4
2
STUBHUB
SIRI
A BEGINNERS GUIDE TO MACHINE LEARNING
WHAT IS IT FOR
▸ Replaces human work
▸ Does things human’s can’t do*
▸ Creates new opportunities
▸ New industries
▸ Innovation
A BEGINNERS GUIDE TO MACHINE LEARNING
WHAT IS IT FOR
▸ Siri / Cortana / Google
▸ Natural Language Processing
▸ Voice and text
▸ How hard would it be to train an Alien to transcribe a
YouTube video?
A BEGINNERS GUIDE TO MACHINE LEARNING
WHO USES IT
▸ Every major company
▸ Nearly everyone connected to the internet
▸ Like the internet it becomes invisible
▸ Transitioning from aiding humans to replacing them
▸ Will you have to use it to stay competitive?
▸ Chess / Go
A BEGINNERS GUIDE TO MACHINE LEARNING
WHO USES IT All posted on Sept 25th
A BEGINNERS GUIDE TO MACHINE LEARNING
EXAMPLES
User Data + ML = Better guidance User Data + ML = Less spam
A BEGINNERS GUIDE TO MACHINE LEARNING
EXAMPLES
User Data + CV + ML = Auto tagged photosComputer Vision + ML = Easy deposit
A BEGINNERS GUIDE TO MACHINE LEARNING
TOOLS TO GET YOU STARTED
▸ As easy as calling an API
▸ Difficult in getting the data
▸ Tutorials are your friend
▸ Strongly advise to start with an idea rather than the
technology
A BEGINNERS GUIDE TO MACHINE LEARNING
TOOLS TO GET YOU STARTED
▸ Generating an idea
▸ Think about the data you have access to
▸ data.gov
▸ dataverse.org
▸ Think about how you are going to label or categorize the
data
A BEGINNERS GUIDE TO MACHINE LEARNING
TOOLS TO GET YOU STARTED
▸ Labeling data
▸ The go-to house example
▸ Can I predict how much a house will cost?
▸ Number of bedrooms, school district …
▸ How do you quantify “school district”?
▸ Algorithms only understand number values*
A BEGINNERS GUIDE TO MACHINE LEARNING
TOOLS TO GET YOU STARTED
▸ Tutorials
▸ cloud.google.com
▸ Udemy, Coursera, Stanford course
▸ Think about what you want to get out of it
▸ Think about your comfort level in math, programming, and
statistics
A BEGINNERS GUIDE TO MACHINE LEARNING
TOOLS TO GET YOU STARTED
▸ APIs from Google, Amazon, Microsoft
▸ Allows you to get started without configuring a dev
environment
▸ If you go TensorFlow locally, go with Docker!
▸ Think about your comfort level
▸ It’s easy to feel in over your head
A BEGINNERS GUIDE TO MACHINE LEARNING
TOOLS TO GET YOU STARTED
▸ Get an idea of something you want to try
▸ Find a tutorial that suites your abilities
▸ Gather data and work to evaluate and clean
▸ Give it a shot!
▸ Don’t worry about the efficacy
▸ Enjoy your new super power!
A BEGINNERS GUIDE TO MACHINE LEARNING
MISCONCEPTIONS
▸ Skynet
▸ We have the ability to intervene
▸ It takes humans to build
▸ Just not there yet
▸ Awareness and knowledge will keep the train on the
tracks
A BEGINNERS GUIDE TO MACHINE LEARNING
MISCONCEPTIONS
▸ What you may not realize
▸ ML is being used to categorize you, and it isn’t perfect
▸ If you aren’t paying for a service you usually are the
product
▸ Know what “data exhaust” you are producing
▸ Privacy has taken a new meaning
A BEGINNERS GUIDE TO MACHINE LEARNING
MISCONCEPTIONS
▸ ML will take jobs and take over
▸ Not quite!
▸ Emotions play an important role
▸ ML / AI are not as close as you may think
▸ We have crossed this bridge before
▸ Art and aesthetic are fickle in society / think marketing
A BEGINNERS GUIDE TO MACHINE LEARNING
THANK YOU!

Contenu connexe

Tendances

Kid Pix And Blue Screening Presentation
Kid Pix And Blue Screening PresentationKid Pix And Blue Screening Presentation
Kid Pix And Blue Screening Presentationjhawtin
 
How to use a 100 year old tactic to boost your productivity today
How to use a 100 year old tactic to boost your productivity todayHow to use a 100 year old tactic to boost your productivity today
How to use a 100 year old tactic to boost your productivity todayKosio Angelov
 
From Photographer to Developer
From Photographer to DeveloperFrom Photographer to Developer
From Photographer to DeveloperAshley McNamara
 
Magazine pre production
Magazine pre productionMagazine pre production
Magazine pre productionJamesSykes17
 
¿Que necesita para ser una buena desarrolladora?
¿Que necesita para ser una buena desarrolladora?¿Que necesita para ser una buena desarrolladora?
¿Que necesita para ser una buena desarrolladora?Software Guru
 
Facilitating Remote Sessions in MURAL
Facilitating Remote Sessions in MURALFacilitating Remote Sessions in MURAL
Facilitating Remote Sessions in MURALMURAL
 
Key takeaways from stanford university
Key takeaways from stanford universityKey takeaways from stanford university
Key takeaways from stanford universityAnuj Magazine
 
Change is a Constant: Technology, Service, and Constant Change
Change is a Constant: Technology, Service, and Constant ChangeChange is a Constant: Technology, Service, and Constant Change
Change is a Constant: Technology, Service, and Constant ChangeEmily Clasper
 
What I learned about innovation (Pragmatic Ideas)
What I learned about innovation (Pragmatic Ideas)What I learned about innovation (Pragmatic Ideas)
What I learned about innovation (Pragmatic Ideas)Lucian Ghinda
 
Innovation is a habit
Innovation is a habitInnovation is a habit
Innovation is a habitEd Kraay
 
Technology Training for Non-Techies
Technology Training for Non-TechiesTechnology Training for Non-Techies
Technology Training for Non-TechiesEmily Clasper
 
7 ways to a winning Investor pitch
7 ways to a winning Investor pitch7 ways to a winning Investor pitch
7 ways to a winning Investor pitchATUL RAJA
 
Making Moodle multi device friendly with bootstrap - Bas brands
Making Moodle multi device friendly with bootstrap - Bas brandsMaking Moodle multi device friendly with bootstrap - Bas brands
Making Moodle multi device friendly with bootstrap - Bas brandsIreland & UK Moodlemoot 2012
 
All Method, No Madness: Guiding Agile Teams Through Research
All Method, No Madness: Guiding Agile Teams Through ResearchAll Method, No Madness: Guiding Agile Teams Through Research
All Method, No Madness: Guiding Agile Teams Through ResearchAggregage
 
Revision techniques for students 2018 v3
Revision techniques for students 2018 v3Revision techniques for students 2018 v3
Revision techniques for students 2018 v3David Drake
 
Obstacles of Digital Transformation Evolution
Obstacles of Digital Transformation EvolutionObstacles of Digital Transformation Evolution
Obstacles of Digital Transformation EvolutionEqual Experts
 
5. pre production(3)
5. pre production(3)5. pre production(3)
5. pre production(3)TheaJennings1
 
Digital Publishing: What to take away
Digital Publishing: What to take awayDigital Publishing: What to take away
Digital Publishing: What to take awayJohannes Henseler
 
Why we fail at ml ai why we fail at ml_ai
Why we fail at ml ai why we fail at ml_aiWhy we fail at ml ai why we fail at ml_ai
Why we fail at ml ai why we fail at ml_aiBrian Ray
 

Tendances (20)

Kid Pix And Blue Screening Presentation
Kid Pix And Blue Screening PresentationKid Pix And Blue Screening Presentation
Kid Pix And Blue Screening Presentation
 
How to use a 100 year old tactic to boost your productivity today
How to use a 100 year old tactic to boost your productivity todayHow to use a 100 year old tactic to boost your productivity today
How to use a 100 year old tactic to boost your productivity today
 
From Photographer to Developer
From Photographer to DeveloperFrom Photographer to Developer
From Photographer to Developer
 
Magazine pre production
Magazine pre productionMagazine pre production
Magazine pre production
 
¿Que necesita para ser una buena desarrolladora?
¿Que necesita para ser una buena desarrolladora?¿Que necesita para ser una buena desarrolladora?
¿Que necesita para ser una buena desarrolladora?
 
Facilitating Remote Sessions in MURAL
Facilitating Remote Sessions in MURALFacilitating Remote Sessions in MURAL
Facilitating Remote Sessions in MURAL
 
Key takeaways from stanford university
Key takeaways from stanford universityKey takeaways from stanford university
Key takeaways from stanford university
 
Change is a Constant: Technology, Service, and Constant Change
Change is a Constant: Technology, Service, and Constant ChangeChange is a Constant: Technology, Service, and Constant Change
Change is a Constant: Technology, Service, and Constant Change
 
What I learned about innovation (Pragmatic Ideas)
What I learned about innovation (Pragmatic Ideas)What I learned about innovation (Pragmatic Ideas)
What I learned about innovation (Pragmatic Ideas)
 
Innovation is a habit
Innovation is a habitInnovation is a habit
Innovation is a habit
 
Technology Training for Non-Techies
Technology Training for Non-TechiesTechnology Training for Non-Techies
Technology Training for Non-Techies
 
7 ways to a winning Investor pitch
7 ways to a winning Investor pitch7 ways to a winning Investor pitch
7 ways to a winning Investor pitch
 
Making Moodle multi device friendly with bootstrap - Bas brands
Making Moodle multi device friendly with bootstrap - Bas brandsMaking Moodle multi device friendly with bootstrap - Bas brands
Making Moodle multi device friendly with bootstrap - Bas brands
 
All Method, No Madness: Guiding Agile Teams Through Research
All Method, No Madness: Guiding Agile Teams Through ResearchAll Method, No Madness: Guiding Agile Teams Through Research
All Method, No Madness: Guiding Agile Teams Through Research
 
Revision techniques for students 2018 v3
Revision techniques for students 2018 v3Revision techniques for students 2018 v3
Revision techniques for students 2018 v3
 
Obstacles of Digital Transformation Evolution
Obstacles of Digital Transformation EvolutionObstacles of Digital Transformation Evolution
Obstacles of Digital Transformation Evolution
 
5. pre production(3)
5. pre production(3)5. pre production(3)
5. pre production(3)
 
The senior dev
The senior devThe senior dev
The senior dev
 
Digital Publishing: What to take away
Digital Publishing: What to take awayDigital Publishing: What to take away
Digital Publishing: What to take away
 
Why we fail at ml ai why we fail at ml_ai
Why we fail at ml ai why we fail at ml_aiWhy we fail at ml ai why we fail at ml_ai
Why we fail at ml ai why we fail at ml_ai
 

Similaire à Machine learning Des Moines (Prairie Code)

Agile: Why it Works, How it Works, and How to Adopt it
Agile: Why it Works, How it Works, and How to Adopt itAgile: Why it Works, How it Works, and How to Adopt it
Agile: Why it Works, How it Works, and How to Adopt itandywalters
 
Growing up your CD Endeavours
Growing up your CD EndeavoursGrowing up your CD Endeavours
Growing up your CD EndeavoursYeong Sheng Tan
 
From Questions to Confidence
From Questions to ConfidenceFrom Questions to Confidence
From Questions to ConfidenceBrent Chudoba
 
Narrated Version Dallas MPUG
Narrated Version Dallas MPUGNarrated Version Dallas MPUG
Narrated Version Dallas MPUGGlen Alleman
 
Scaling engineering teams
Scaling engineering teamsScaling engineering teams
Scaling engineering teamsFrank Lamantia
 
Free and Open Machine Learning
Free and Open Machine LearningFree and Open Machine Learning
Free and Open Machine LearningMaikel Mardjan
 
DevOps role in engineering organization (Dive into DevOps)
DevOps role in engineering organization (Dive into DevOps)DevOps role in engineering organization (Dive into DevOps)
DevOps role in engineering organization (Dive into DevOps)Provectus
 
Week3 day3slide
Week3 day3slideWeek3 day3slide
Week3 day3slideRohitKar2
 
Open source-saturdays
Open source-saturdaysOpen source-saturdays
Open source-saturdaysTejas Bubane
 
A Journey of Android Engineer in Start-up Culture
A Journey of Android Engineer in Start-up CultureA Journey of Android Engineer in Start-up Culture
A Journey of Android Engineer in Start-up CultureFatima Azzahro
 
Enterprise Frameworks: Java & .NET
Enterprise Frameworks: Java & .NETEnterprise Frameworks: Java & .NET
Enterprise Frameworks: Java & .NETAnant Corporation
 
Manifesto-Driven Development - TexasCamp 2018
Manifesto-Driven Development - TexasCamp 2018Manifesto-Driven Development - TexasCamp 2018
Manifesto-Driven Development - TexasCamp 2018Paul Grotevant
 
Developer's Introduction to Machine Learning
Developer's Introduction to Machine LearningDeveloper's Introduction to Machine Learning
Developer's Introduction to Machine LearningChristopher Mohritz
 
Machine Learning: Expertise On-Demand
Machine Learning: Expertise On-DemandMachine Learning: Expertise On-Demand
Machine Learning: Expertise On-DemandChristopher Mohritz
 
San Francisco Hacker News - Machine Learning for Hackers
San Francisco Hacker News - Machine Learning for HackersSan Francisco Hacker News - Machine Learning for Hackers
San Francisco Hacker News - Machine Learning for HackersAdam Gibson
 
Machine learning and_buzzwords
Machine learning and_buzzwordsMachine learning and_buzzwords
Machine learning and_buzzwordsRajarshi Dutta
 

Similaire à Machine learning Des Moines (Prairie Code) (20)

Agile: Why it Works, How it Works, and How to Adopt it
Agile: Why it Works, How it Works, and How to Adopt itAgile: Why it Works, How it Works, and How to Adopt it
Agile: Why it Works, How it Works, and How to Adopt it
 
Growing up your CD Endeavours
Growing up your CD EndeavoursGrowing up your CD Endeavours
Growing up your CD Endeavours
 
From Questions to Confidence
From Questions to ConfidenceFrom Questions to Confidence
From Questions to Confidence
 
Narrated Version Dallas MPUG
Narrated Version Dallas MPUGNarrated Version Dallas MPUG
Narrated Version Dallas MPUG
 
Pair programming
Pair programmingPair programming
Pair programming
 
Tf wiads
Tf wiadsTf wiads
Tf wiads
 
Scaling engineering teams
Scaling engineering teamsScaling engineering teams
Scaling engineering teams
 
Free and Open Machine Learning
Free and Open Machine LearningFree and Open Machine Learning
Free and Open Machine Learning
 
DevOps role in engineering organization (Dive into DevOps)
DevOps role in engineering organization (Dive into DevOps)DevOps role in engineering organization (Dive into DevOps)
DevOps role in engineering organization (Dive into DevOps)
 
Week3 day3slide
Week3 day3slideWeek3 day3slide
Week3 day3slide
 
The Making of a Web Team (Notes)
The Making of a Web Team (Notes)The Making of a Web Team (Notes)
The Making of a Web Team (Notes)
 
Open source-saturdays
Open source-saturdaysOpen source-saturdays
Open source-saturdays
 
A Journey of Android Engineer in Start-up Culture
A Journey of Android Engineer in Start-up CultureA Journey of Android Engineer in Start-up Culture
A Journey of Android Engineer in Start-up Culture
 
Enterprise Frameworks: Java & .NET
Enterprise Frameworks: Java & .NETEnterprise Frameworks: Java & .NET
Enterprise Frameworks: Java & .NET
 
Manifesto-Driven Development - TexasCamp 2018
Manifesto-Driven Development - TexasCamp 2018Manifesto-Driven Development - TexasCamp 2018
Manifesto-Driven Development - TexasCamp 2018
 
Developer's Introduction to Machine Learning
Developer's Introduction to Machine LearningDeveloper's Introduction to Machine Learning
Developer's Introduction to Machine Learning
 
Machine Learning: Expertise On-Demand
Machine Learning: Expertise On-DemandMachine Learning: Expertise On-Demand
Machine Learning: Expertise On-Demand
 
Happier Teams Through Tools
Happier Teams Through ToolsHappier Teams Through Tools
Happier Teams Through Tools
 
San Francisco Hacker News - Machine Learning for Hackers
San Francisco Hacker News - Machine Learning for HackersSan Francisco Hacker News - Machine Learning for Hackers
San Francisco Hacker News - Machine Learning for Hackers
 
Machine learning and_buzzwords
Machine learning and_buzzwordsMachine learning and_buzzwords
Machine learning and_buzzwords
 

Dernier

COMPUTER 10: Lesson 7 - File Storage and Online Collaboration
COMPUTER 10: Lesson 7 - File Storage and Online CollaborationCOMPUTER 10: Lesson 7 - File Storage and Online Collaboration
COMPUTER 10: Lesson 7 - File Storage and Online Collaborationbruanjhuli
 
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdfIaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdfDaniel Santiago Silva Capera
 
Introduction to Matsuo Laboratory (ENG).pptx
Introduction to Matsuo Laboratory (ENG).pptxIntroduction to Matsuo Laboratory (ENG).pptx
Introduction to Matsuo Laboratory (ENG).pptxMatsuo Lab
 
Empowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership BlueprintEmpowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership BlueprintMahmoud Rabie
 
Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)Commit University
 
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve DecarbonizationUsing IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve DecarbonizationIES VE
 
UiPath Platform: The Backend Engine Powering Your Automation - Session 1
UiPath Platform: The Backend Engine Powering Your Automation - Session 1UiPath Platform: The Backend Engine Powering Your Automation - Session 1
UiPath Platform: The Backend Engine Powering Your Automation - Session 1DianaGray10
 
Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024D Cloud Solutions
 
UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6DianaGray10
 
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfJamie (Taka) Wang
 
UiPath Studio Web workshop series - Day 8
UiPath Studio Web workshop series - Day 8UiPath Studio Web workshop series - Day 8
UiPath Studio Web workshop series - Day 8DianaGray10
 
Videogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfVideogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfinfogdgmi
 
UiPath Studio Web workshop series - Day 7
UiPath Studio Web workshop series - Day 7UiPath Studio Web workshop series - Day 7
UiPath Studio Web workshop series - Day 7DianaGray10
 
How Accurate are Carbon Emissions Projections?
How Accurate are Carbon Emissions Projections?How Accurate are Carbon Emissions Projections?
How Accurate are Carbon Emissions Projections?IES VE
 
Salesforce Miami User Group Event - 1st Quarter 2024
Salesforce Miami User Group Event - 1st Quarter 2024Salesforce Miami User Group Event - 1st Quarter 2024
Salesforce Miami User Group Event - 1st Quarter 2024SkyPlanner
 
Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1DianaGray10
 
Machine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdfMachine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdfAijun Zhang
 
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019IES VE
 
Meet the new FSP 3000 M-Flex800™
Meet the new FSP 3000 M-Flex800™Meet the new FSP 3000 M-Flex800™
Meet the new FSP 3000 M-Flex800™Adtran
 

Dernier (20)

COMPUTER 10: Lesson 7 - File Storage and Online Collaboration
COMPUTER 10: Lesson 7 - File Storage and Online CollaborationCOMPUTER 10: Lesson 7 - File Storage and Online Collaboration
COMPUTER 10: Lesson 7 - File Storage and Online Collaboration
 
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdfIaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
 
Introduction to Matsuo Laboratory (ENG).pptx
Introduction to Matsuo Laboratory (ENG).pptxIntroduction to Matsuo Laboratory (ENG).pptx
Introduction to Matsuo Laboratory (ENG).pptx
 
Empowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership BlueprintEmpowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership Blueprint
 
Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)
 
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve DecarbonizationUsing IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
 
UiPath Platform: The Backend Engine Powering Your Automation - Session 1
UiPath Platform: The Backend Engine Powering Your Automation - Session 1UiPath Platform: The Backend Engine Powering Your Automation - Session 1
UiPath Platform: The Backend Engine Powering Your Automation - Session 1
 
201610817 - edge part1
201610817 - edge part1201610817 - edge part1
201610817 - edge part1
 
Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024
 
UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6
 
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
 
UiPath Studio Web workshop series - Day 8
UiPath Studio Web workshop series - Day 8UiPath Studio Web workshop series - Day 8
UiPath Studio Web workshop series - Day 8
 
Videogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfVideogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdf
 
UiPath Studio Web workshop series - Day 7
UiPath Studio Web workshop series - Day 7UiPath Studio Web workshop series - Day 7
UiPath Studio Web workshop series - Day 7
 
How Accurate are Carbon Emissions Projections?
How Accurate are Carbon Emissions Projections?How Accurate are Carbon Emissions Projections?
How Accurate are Carbon Emissions Projections?
 
Salesforce Miami User Group Event - 1st Quarter 2024
Salesforce Miami User Group Event - 1st Quarter 2024Salesforce Miami User Group Event - 1st Quarter 2024
Salesforce Miami User Group Event - 1st Quarter 2024
 
Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1
 
Machine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdfMachine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdf
 
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
 
Meet the new FSP 3000 M-Flex800™
Meet the new FSP 3000 M-Flex800™Meet the new FSP 3000 M-Flex800™
Meet the new FSP 3000 M-Flex800™
 

Machine learning Des Moines (Prairie Code)

  • 2. A BEGINNERS GUIDE TO MACHINE LEARNING INTRODUCTION: ANDREW RANGEL ▸ Background: Mobile Development ▸ Passion for new and exciting technologies ▸ Machine Learning (ML) for ~1 year ▸ Passion for education and teaching others
  • 3. A BEGINNERS GUIDE TO MACHINE LEARNING INTRODUCTION: MACHINE LEARNING ▸ What is it ▸ What is it for ▸ Who uses it ▸ Examples ▸ Tools to get started ▸ Misconceptions
  • 4. A BEGINNERS GUIDE TO MACHINE LEARNING INTRODUCTION: MACHINE LEARNING ▸ Scary! ▸ Math. Math. MATH! ▸ There are a set of basic elements ▸ Learning the mechanisms can elevate your career
  • 5. A BEGINNERS GUIDE TO MACHINE LEARNING WHAT IS IT ▸ Using algorithms to parse data and make a prediction about the world ▸ Came from early (’56!) Artificial Intelligence minds ▸ An early use was Computer Vision ▸ ML / AI / CV / NN ▸ Training ▸ Not being told “what to do”
  • 6. A BEGINNERS GUIDE TO MACHINE LEARNING WHAT IS IT ▸ Linear Regression
  • 7. A BEGINNERS GUIDE TO MACHINE LEARNING WHAT IS IT ▸ Linear Regression $12
  • 8. A BEGINNERS GUIDE TO MACHINE LEARNING WHAT IS IT ▸ Gradient Discent
  • 9. A BEGINNERS GUIDE TO MACHINE LEARNING WHAT IS IT FOR AUDIO TEXT EVALUATE SCORE RESPOND ERRORWEIGHTS “Hey Siri what is the score of the Chiefs game?” Chiefs Game Score 10 4 2
  • 10. A BEGINNERS GUIDE TO MACHINE LEARNING WHAT IS IT FOR AUDIO TEXT EVALUATE SCORE RESPOND ERRORWEIGHTS “Hey Siri what is the score of the Chiefs game?” Chiefs Game Score 10 4 2 STUBHUB SIRI
  • 11. A BEGINNERS GUIDE TO MACHINE LEARNING WHAT IS IT FOR ▸ Replaces human work ▸ Does things human’s can’t do* ▸ Creates new opportunities ▸ New industries ▸ Innovation
  • 12. A BEGINNERS GUIDE TO MACHINE LEARNING WHAT IS IT FOR ▸ Siri / Cortana / Google ▸ Natural Language Processing ▸ Voice and text ▸ How hard would it be to train an Alien to transcribe a YouTube video?
  • 13. A BEGINNERS GUIDE TO MACHINE LEARNING WHO USES IT ▸ Every major company ▸ Nearly everyone connected to the internet ▸ Like the internet it becomes invisible ▸ Transitioning from aiding humans to replacing them ▸ Will you have to use it to stay competitive? ▸ Chess / Go
  • 14. A BEGINNERS GUIDE TO MACHINE LEARNING WHO USES IT All posted on Sept 25th
  • 15. A BEGINNERS GUIDE TO MACHINE LEARNING EXAMPLES User Data + ML = Better guidance User Data + ML = Less spam
  • 16. A BEGINNERS GUIDE TO MACHINE LEARNING EXAMPLES User Data + CV + ML = Auto tagged photosComputer Vision + ML = Easy deposit
  • 17. A BEGINNERS GUIDE TO MACHINE LEARNING TOOLS TO GET YOU STARTED ▸ As easy as calling an API ▸ Difficult in getting the data ▸ Tutorials are your friend ▸ Strongly advise to start with an idea rather than the technology
  • 18. A BEGINNERS GUIDE TO MACHINE LEARNING TOOLS TO GET YOU STARTED ▸ Generating an idea ▸ Think about the data you have access to ▸ data.gov ▸ dataverse.org ▸ Think about how you are going to label or categorize the data
  • 19. A BEGINNERS GUIDE TO MACHINE LEARNING TOOLS TO GET YOU STARTED ▸ Labeling data ▸ The go-to house example ▸ Can I predict how much a house will cost? ▸ Number of bedrooms, school district … ▸ How do you quantify “school district”? ▸ Algorithms only understand number values*
  • 20. A BEGINNERS GUIDE TO MACHINE LEARNING TOOLS TO GET YOU STARTED ▸ Tutorials ▸ cloud.google.com ▸ Udemy, Coursera, Stanford course ▸ Think about what you want to get out of it ▸ Think about your comfort level in math, programming, and statistics
  • 21. A BEGINNERS GUIDE TO MACHINE LEARNING TOOLS TO GET YOU STARTED ▸ APIs from Google, Amazon, Microsoft ▸ Allows you to get started without configuring a dev environment ▸ If you go TensorFlow locally, go with Docker! ▸ Think about your comfort level ▸ It’s easy to feel in over your head
  • 22. A BEGINNERS GUIDE TO MACHINE LEARNING TOOLS TO GET YOU STARTED ▸ Get an idea of something you want to try ▸ Find a tutorial that suites your abilities ▸ Gather data and work to evaluate and clean ▸ Give it a shot! ▸ Don’t worry about the efficacy ▸ Enjoy your new super power!
  • 23. A BEGINNERS GUIDE TO MACHINE LEARNING MISCONCEPTIONS ▸ Skynet ▸ We have the ability to intervene ▸ It takes humans to build ▸ Just not there yet ▸ Awareness and knowledge will keep the train on the tracks
  • 24. A BEGINNERS GUIDE TO MACHINE LEARNING MISCONCEPTIONS ▸ What you may not realize ▸ ML is being used to categorize you, and it isn’t perfect ▸ If you aren’t paying for a service you usually are the product ▸ Know what “data exhaust” you are producing ▸ Privacy has taken a new meaning
  • 25. A BEGINNERS GUIDE TO MACHINE LEARNING MISCONCEPTIONS ▸ ML will take jobs and take over ▸ Not quite! ▸ Emotions play an important role ▸ ML / AI are not as close as you may think ▸ We have crossed this bridge before ▸ Art and aesthetic are fickle in society / think marketing
  • 26. A BEGINNERS GUIDE TO MACHINE LEARNING THANK YOU!