SlideShare a Scribd company logo

An explanation of machine learning for business

Slides of the course on big data by Clement Levallois from EMLYON Business School. For business students. Check the online video connected with these slides. -> Machine learning explained in simple terms to a business audience: what is a training set, a test set, and how does machine learning differ from statistics.

1 of 8
Download to read offline
MK99 – Big Data 
1 
Big data & cross-platform analytics 
MOOC lectures Pr. Clement Levallois
MK99 – Big Data 
2 
A short note on machine learning for business
MK99 – Big Data 
3 
Machine Learning 
• Family of techniques to formulate predictions, based on data 
•Why is it called Machine learning? 
–Machine: it is about algorithms running on computers, not equations solved with pen and paper 
–Learning: the algorithms start with zero accuracy. Then, they get more accurate while being fed with data: the algorithm refines its parameters, it “learns”.
MK99 – Big Data 
4 
Typical set up 
1.We start with a training set 
Data already collected: we know the actual values to be found 
Ex: a list of consumers, their characteristics and their associated credit score 
2.The algorithms are trained on this set 
-> A series of algorithms run on the training set. Their parameters get adjusted so that the actual values get progressively predicted the most accurately possible. 
3.A test set (“fresh data”) is brought 
-> List of consumer characteristics. Their credit score is known but hidden. 
4.Running the trained algo on the test set 
-> Predict the credit score for each consumer in the test set, using the algorithms that were trained on phase 1 
5.A measure of accuracy 
- Given the correct values to be predicted in the test set, how accurate were the algorithms? 
-> Where the credit scores accurately predicted? 
Actual values
MK99 – Big Data 
5 
Vocabulary 
•Data scientists “train” their model and then test it 
•They are concerned by “out-of-sample” prediction 
–The fact that their model predicts accurately data points in the training set (the “sample”) is trivial 
–This is the accuracy on the test set that matters! 
–This is called an “out-of-sample” prediction
MK99 – Big Data 
6 
Why is machine learning (ML) so different from statistics? 
•ML does not focus on causality – just prediction! 
–Note: for this reason, ML cannot predict the effect of intervention - it has no causal model. 
•ML has a special concern for out-of-sample prediction 
–Will be especially careful about over-fitting 
•ML picks its algorithms from diff academic disciplines 
–Text, network relations, clustering, not just traditional statistics 
•Coming from comput. sciences, ML has affinities with big data 
–Procedures optimized for speed and scale 
But the best data scientists often started as statisticians / econometricians: 
See Hal Varian: Chief Economist at Google

Recommended

How Machine Learning Works for Business
How Machine Learning Works for BusinessHow Machine Learning Works for Business
How Machine Learning Works for Business10x Nation
 
AutoML - The Future of AI
AutoML - The Future of AIAutoML - The Future of AI
AutoML - The Future of AINing Jiang
 
Lecture 3: Basic Concepts of Machine Learning - Induction & Evaluation
Lecture 3: Basic Concepts of Machine Learning - Induction & EvaluationLecture 3: Basic Concepts of Machine Learning - Induction & Evaluation
Lecture 3: Basic Concepts of Machine Learning - Induction & EvaluationMarina Santini
 
Business Intelligence Presentation 1 (15th March'16)
Business Intelligence Presentation 1 (15th March'16)Business Intelligence Presentation 1 (15th March'16)
Business Intelligence Presentation 1 (15th March'16)Muhammad Fahad
 
Automated Machine Learning
Automated Machine LearningAutomated Machine Learning
Automated Machine LearningYuriy Guts
 
Automatic Machine Learning, AutoML
Automatic Machine Learning, AutoMLAutomatic Machine Learning, AutoML
Automatic Machine Learning, AutoMLHimadri Mishra
 
Business Intelligence & Predictive Analytic by Prof. Lili Saghafi
Business Intelligence & Predictive Analytic by Prof. Lili SaghafiBusiness Intelligence & Predictive Analytic by Prof. Lili Saghafi
Business Intelligence & Predictive Analytic by Prof. Lili SaghafiProfessor Lili Saghafi
 

More Related Content

What's hot

K-Folds Cross Validation Method
K-Folds Cross Validation MethodK-Folds Cross Validation Method
K-Folds Cross Validation MethodSHUBHAM GUPTA
 
Dimensionality Reduction
Dimensionality ReductionDimensionality Reduction
Dimensionality ReductionSaad Elbeleidy
 
An introduction to Business intelligence
An introduction to Business intelligenceAn introduction to Business intelligence
An introduction to Business intelligenceHadi Fadlallah
 
Automated Machine Learning (Auto ML)
Automated Machine Learning (Auto ML)Automated Machine Learning (Auto ML)
Automated Machine Learning (Auto ML)Hayim Makabee
 
LeanIX & LoQutus: Next generation Enterprise Architecture Management
LeanIX & LoQutus: Next generation Enterprise Architecture ManagementLeanIX & LoQutus: Next generation Enterprise Architecture Management
LeanIX & LoQutus: Next generation Enterprise Architecture ManagementLoQutus
 
Machine Learning
Machine LearningMachine Learning
Machine LearningKumar P
 
Optimization in Deep Learning
Optimization in Deep LearningOptimization in Deep Learning
Optimization in Deep LearningYan Xu
 
Feature Engineering
Feature EngineeringFeature Engineering
Feature EngineeringHJ van Veen
 
Significance of Data Mining
Significance of Data MiningSignificance of Data Mining
Significance of Data Mining8trackweb
 
Introduction to Business Intelligence
Introduction to Business IntelligenceIntroduction to Business Intelligence
Introduction to Business IntelligenceAlmog Ramrajkar
 
Simple Introduction to AutoEncoder
Simple Introduction to AutoEncoderSimple Introduction to AutoEncoder
Simple Introduction to AutoEncoderJun Lang
 
USE OF DATA MINING IN BANKING SECTOR
USE OF DATA MINING IN BANKING SECTORUSE OF DATA MINING IN BANKING SECTOR
USE OF DATA MINING IN BANKING SECTORarpit bhadoriya
 
Clustering for Stream and Parallelism (DATA ANALYTICS)
Clustering for Stream and Parallelism (DATA ANALYTICS)Clustering for Stream and Parallelism (DATA ANALYTICS)
Clustering for Stream and Parallelism (DATA ANALYTICS)DheerajPachauri
 
Predictive Analytics: Context and Use Cases
Predictive Analytics: Context and Use CasesPredictive Analytics: Context and Use Cases
Predictive Analytics: Context and Use CasesKimberley Mitchell
 
Introduction to Real-time data processing
Introduction to Real-time data processingIntroduction to Real-time data processing
Introduction to Real-time data processingYogi Devendra Vyavahare
 
Machine Learning Introduction
Machine Learning IntroductionMachine Learning Introduction
Machine Learning IntroductionYounesCharfaoui
 

What's hot (20)

Semantic AI
Semantic AISemantic AI
Semantic AI
 
K-Folds Cross Validation Method
K-Folds Cross Validation MethodK-Folds Cross Validation Method
K-Folds Cross Validation Method
 
Dimensionality Reduction
Dimensionality ReductionDimensionality Reduction
Dimensionality Reduction
 
An introduction to Business intelligence
An introduction to Business intelligenceAn introduction to Business intelligence
An introduction to Business intelligence
 
Automated Machine Learning (Auto ML)
Automated Machine Learning (Auto ML)Automated Machine Learning (Auto ML)
Automated Machine Learning (Auto ML)
 
Datawarehouse olap olam
Datawarehouse olap olamDatawarehouse olap olam
Datawarehouse olap olam
 
Dimensionality reduction
Dimensionality reductionDimensionality reduction
Dimensionality reduction
 
LeanIX & LoQutus: Next generation Enterprise Architecture Management
LeanIX & LoQutus: Next generation Enterprise Architecture ManagementLeanIX & LoQutus: Next generation Enterprise Architecture Management
LeanIX & LoQutus: Next generation Enterprise Architecture Management
 
Machine Learning
Machine LearningMachine Learning
Machine Learning
 
Optimization in Deep Learning
Optimization in Deep LearningOptimization in Deep Learning
Optimization in Deep Learning
 
Feature Engineering
Feature EngineeringFeature Engineering
Feature Engineering
 
Significance of Data Mining
Significance of Data MiningSignificance of Data Mining
Significance of Data Mining
 
Introduction to Business Intelligence
Introduction to Business IntelligenceIntroduction to Business Intelligence
Introduction to Business Intelligence
 
Simple Introduction to AutoEncoder
Simple Introduction to AutoEncoderSimple Introduction to AutoEncoder
Simple Introduction to AutoEncoder
 
Machine learning
Machine learningMachine learning
Machine learning
 
USE OF DATA MINING IN BANKING SECTOR
USE OF DATA MINING IN BANKING SECTORUSE OF DATA MINING IN BANKING SECTOR
USE OF DATA MINING IN BANKING SECTOR
 
Clustering for Stream and Parallelism (DATA ANALYTICS)
Clustering for Stream and Parallelism (DATA ANALYTICS)Clustering for Stream and Parallelism (DATA ANALYTICS)
Clustering for Stream and Parallelism (DATA ANALYTICS)
 
Predictive Analytics: Context and Use Cases
Predictive Analytics: Context and Use CasesPredictive Analytics: Context and Use Cases
Predictive Analytics: Context and Use Cases
 
Introduction to Real-time data processing
Introduction to Real-time data processingIntroduction to Real-time data processing
Introduction to Real-time data processing
 
Machine Learning Introduction
Machine Learning IntroductionMachine Learning Introduction
Machine Learning Introduction
 

Viewers also liked

Introduction to Machine Learning
Introduction to Machine LearningIntroduction to Machine Learning
Introduction to Machine LearningLior Rokach
 
Transparent Machine Learning for Information Extraction: State-of-the-Art and...
Transparent Machine Learning for Information Extraction: State-of-the-Art and...Transparent Machine Learning for Information Extraction: State-of-the-Art and...
Transparent Machine Learning for Information Extraction: State-of-the-Art and...Yunyao Li
 
Machine learning
Machine learningMachine learning
Machine learningInfoFarm
 
Machine learning ~ Forecasting
Machine learning ~ ForecastingMachine learning ~ Forecasting
Machine learning ~ ForecastingShaswat Mandhanya
 
An introduction to Machine Learning (and a little bit of Deep Learning)
An introduction to Machine Learning (and a little bit of Deep Learning)An introduction to Machine Learning (and a little bit of Deep Learning)
An introduction to Machine Learning (and a little bit of Deep Learning)Thomas da Silva Paula
 
An introduction to Machine Learning
An introduction to Machine LearningAn introduction to Machine Learning
An introduction to Machine Learningbutest
 
Transform your Business with AI, Deep Learning and Machine Learning
Transform your Business with AI, Deep Learning and Machine LearningTransform your Business with AI, Deep Learning and Machine Learning
Transform your Business with AI, Deep Learning and Machine LearningSri Ambati
 
Introduction to Machine Learning
Introduction to Machine LearningIntroduction to Machine Learning
Introduction to Machine LearningRahul Jain
 

Viewers also liked (10)

Introduction to Machine Learning
Introduction to Machine LearningIntroduction to Machine Learning
Introduction to Machine Learning
 
Transparent Machine Learning for Information Extraction: State-of-the-Art and...
Transparent Machine Learning for Information Extraction: State-of-the-Art and...Transparent Machine Learning for Information Extraction: State-of-the-Art and...
Transparent Machine Learning for Information Extraction: State-of-the-Art and...
 
Machine learning
Machine learningMachine learning
Machine learning
 
L1. State of the Art in Machine Learning
L1. State of the Art in Machine LearningL1. State of the Art in Machine Learning
L1. State of the Art in Machine Learning
 
Machine learning ~ Forecasting
Machine learning ~ ForecastingMachine learning ~ Forecasting
Machine learning ~ Forecasting
 
An introduction to Machine Learning (and a little bit of Deep Learning)
An introduction to Machine Learning (and a little bit of Deep Learning)An introduction to Machine Learning (and a little bit of Deep Learning)
An introduction to Machine Learning (and a little bit of Deep Learning)
 
An introduction to Machine Learning
An introduction to Machine LearningAn introduction to Machine Learning
An introduction to Machine Learning
 
Transform your Business with AI, Deep Learning and Machine Learning
Transform your Business with AI, Deep Learning and Machine LearningTransform your Business with AI, Deep Learning and Machine Learning
Transform your Business with AI, Deep Learning and Machine Learning
 
Introduction to Machine Learning
Introduction to Machine LearningIntroduction to Machine Learning
Introduction to Machine Learning
 
Machine Learning for Dummies
Machine Learning for DummiesMachine Learning for Dummies
Machine Learning for Dummies
 

Similar to An explanation of machine learning for business

Introduction to ML (Machine Learning)
Introduction to ML (Machine Learning)Introduction to ML (Machine Learning)
Introduction to ML (Machine Learning)SwatiTripathi44
 
Machine learning
Machine learningMachine learning
Machine learningdeepakbagam
 
Pricing like a data scientist
Pricing like a data scientistPricing like a data scientist
Pricing like a data scientistMatthew Evans
 
Machine Learning and Analytics in Splunk
Machine Learning and Analytics in SplunkMachine Learning and Analytics in Splunk
Machine Learning and Analytics in SplunkSplunk
 
Machine Learning and Analytics Breakout Session
Machine Learning and Analytics Breakout SessionMachine Learning and Analytics Breakout Session
Machine Learning and Analytics Breakout SessionSplunk
 
Course 2 Machine Learning Data LifeCycle in Production - Week 1
Course 2   Machine Learning Data LifeCycle in Production - Week 1Course 2   Machine Learning Data LifeCycle in Production - Week 1
Course 2 Machine Learning Data LifeCycle in Production - Week 1Ajay Taneja
 
Choosing a Machine Learning technique to solve your need
Choosing a Machine Learning technique to solve your needChoosing a Machine Learning technique to solve your need
Choosing a Machine Learning technique to solve your needGibDevs
 
Machine Learning with Big Data using Apache Spark
Machine Learning with Big Data using Apache SparkMachine Learning with Big Data using Apache Spark
Machine Learning with Big Data using Apache SparkInSemble
 
Barga Data Science lecture 10
Barga Data Science lecture 10Barga Data Science lecture 10
Barga Data Science lecture 10Roger Barga
 
AI-900 - Fundamental Principles of ML.pptx
AI-900 - Fundamental Principles of ML.pptxAI-900 - Fundamental Principles of ML.pptx
AI-900 - Fundamental Principles of ML.pptxkprasad8
 
Machine Learning and Analytics Breakout Session
Machine Learning and Analytics Breakout SessionMachine Learning and Analytics Breakout Session
Machine Learning and Analytics Breakout SessionSplunk
 
Experimental Design for Distributed Machine Learning with Myles Baker
Experimental Design for Distributed Machine Learning with Myles BakerExperimental Design for Distributed Machine Learning with Myles Baker
Experimental Design for Distributed Machine Learning with Myles BakerDatabricks
 
Machine learning and big data
Machine learning and big dataMachine learning and big data
Machine learning and big dataPoo Kuan Hoong
 
Big data expo - machine learning in the elastic stack
Big data expo - machine learning in the elastic stack Big data expo - machine learning in the elastic stack
Big data expo - machine learning in the elastic stack BigDataExpo
 
Supervised learning techniques and applications
Supervised learning techniques and applicationsSupervised learning techniques and applications
Supervised learning techniques and applicationsBenjaminlapid1
 
Unit 1-ML (1) (1).pptx
Unit 1-ML (1) (1).pptxUnit 1-ML (1) (1).pptx
Unit 1-ML (1) (1).pptxChitrachitrap
 

Similar to An explanation of machine learning for business (20)

Introduction to ML (Machine Learning)
Introduction to ML (Machine Learning)Introduction to ML (Machine Learning)
Introduction to ML (Machine Learning)
 
ML_Module_1.pdf
ML_Module_1.pdfML_Module_1.pdf
ML_Module_1.pdf
 
Machine learning
Machine learningMachine learning
Machine learning
 
Pricing like a data scientist
Pricing like a data scientistPricing like a data scientist
Pricing like a data scientist
 
Machine Learning and Analytics in Splunk
Machine Learning and Analytics in SplunkMachine Learning and Analytics in Splunk
Machine Learning and Analytics in Splunk
 
Machine Learning and Analytics Breakout Session
Machine Learning and Analytics Breakout SessionMachine Learning and Analytics Breakout Session
Machine Learning and Analytics Breakout Session
 
Course 2 Machine Learning Data LifeCycle in Production - Week 1
Course 2   Machine Learning Data LifeCycle in Production - Week 1Course 2   Machine Learning Data LifeCycle in Production - Week 1
Course 2 Machine Learning Data LifeCycle in Production - Week 1
 
Choosing a Machine Learning technique to solve your need
Choosing a Machine Learning technique to solve your needChoosing a Machine Learning technique to solve your need
Choosing a Machine Learning technique to solve your need
 
Machine Learning_Unit 2_Full.ppt.pdf
Machine Learning_Unit 2_Full.ppt.pdfMachine Learning_Unit 2_Full.ppt.pdf
Machine Learning_Unit 2_Full.ppt.pdf
 
Machine Learning with Big Data using Apache Spark
Machine Learning with Big Data using Apache SparkMachine Learning with Big Data using Apache Spark
Machine Learning with Big Data using Apache Spark
 
Barga Data Science lecture 10
Barga Data Science lecture 10Barga Data Science lecture 10
Barga Data Science lecture 10
 
AI-900 - Fundamental Principles of ML.pptx
AI-900 - Fundamental Principles of ML.pptxAI-900 - Fundamental Principles of ML.pptx
AI-900 - Fundamental Principles of ML.pptx
 
Machine Learning and Analytics Breakout Session
Machine Learning and Analytics Breakout SessionMachine Learning and Analytics Breakout Session
Machine Learning and Analytics Breakout Session
 
Experimental Design for Distributed Machine Learning with Myles Baker
Experimental Design for Distributed Machine Learning with Myles BakerExperimental Design for Distributed Machine Learning with Myles Baker
Experimental Design for Distributed Machine Learning with Myles Baker
 
Machine learning and big data
Machine learning and big dataMachine learning and big data
Machine learning and big data
 
Big data expo - machine learning in the elastic stack
Big data expo - machine learning in the elastic stack Big data expo - machine learning in the elastic stack
Big data expo - machine learning in the elastic stack
 
Machine learning
Machine learningMachine learning
Machine learning
 
ML PPT-1.pptx
ML PPT-1.pptxML PPT-1.pptx
ML PPT-1.pptx
 
Supervised learning techniques and applications
Supervised learning techniques and applicationsSupervised learning techniques and applications
Supervised learning techniques and applications
 
Unit 1-ML (1) (1).pptx
Unit 1-ML (1) (1).pptxUnit 1-ML (1) (1).pptx
Unit 1-ML (1) (1).pptx
 

More from Clement Levallois

Part 2: covid-19 on Twitter, with a focus on 3 new seed accounts
Part 2: covid-19 on Twitter, with a focus on 3 new seed accountsPart 2: covid-19 on Twitter, with a focus on 3 new seed accounts
Part 2: covid-19 on Twitter, with a focus on 3 new seed accountsClement Levallois
 
Education et intelligence artificielle
Education et intelligence artificielleEducation et intelligence artificielle
Education et intelligence artificielleClement Levallois
 
3 familles d'intelligence artificielle et leurs applications business
3 familles d'intelligence artificielle et leurs applications business3 familles d'intelligence artificielle et leurs applications business
3 familles d'intelligence artificielle et leurs applications businessClement Levallois
 
Présentation FrenchWeb: Qu'est-ce que la visualisation des données?
Présentation FrenchWeb: Qu'est-ce que la visualisation des données?Présentation FrenchWeb: Qu'est-ce que la visualisation des données?
Présentation FrenchWeb: Qu'est-ce que la visualisation des données?Clement Levallois
 
Presentation of programming languages for beginners
Presentation of programming languages for beginnersPresentation of programming languages for beginners
Presentation of programming languages for beginnersClement Levallois
 
Umigon: crowdsourcing in the classroom
Umigon: crowdsourcing in the classroomUmigon: crowdsourcing in the classroom
Umigon: crowdsourcing in the classroomClement Levallois
 
Data visualization: enjeux pour le business
Data visualization: enjeux pour le businessData visualization: enjeux pour le business
Data visualization: enjeux pour le businessClement Levallois
 
A Primer on Text Mining for Business
A Primer on Text Mining for BusinessA Primer on Text Mining for Business
A Primer on Text Mining for BusinessClement Levallois
 
The business stakes of data integration
The business stakes of data integrationThe business stakes of data integration
The business stakes of data integrationClement Levallois
 

More from Clement Levallois (13)

Part 2: covid-19 on Twitter, with a focus on 3 new seed accounts
Part 2: covid-19 on Twitter, with a focus on 3 new seed accountsPart 2: covid-19 on Twitter, with a focus on 3 new seed accounts
Part 2: covid-19 on Twitter, with a focus on 3 new seed accounts
 
Education et intelligence artificielle
Education et intelligence artificielleEducation et intelligence artificielle
Education et intelligence artificielle
 
3 familles d'intelligence artificielle et leurs applications business
3 familles d'intelligence artificielle et leurs applications business3 familles d'intelligence artificielle et leurs applications business
3 familles d'intelligence artificielle et leurs applications business
 
Présentation FrenchWeb: Qu'est-ce que la visualisation des données?
Présentation FrenchWeb: Qu'est-ce que la visualisation des données?Présentation FrenchWeb: Qu'est-ce que la visualisation des données?
Présentation FrenchWeb: Qu'est-ce que la visualisation des données?
 
Presentation of programming languages for beginners
Presentation of programming languages for beginnersPresentation of programming languages for beginners
Presentation of programming languages for beginners
 
Umigon: crowdsourcing in the classroom
Umigon: crowdsourcing in the classroomUmigon: crowdsourcing in the classroom
Umigon: crowdsourcing in the classroom
 
Data visualization: enjeux pour le business
Data visualization: enjeux pour le businessData visualization: enjeux pour le business
Data visualization: enjeux pour le business
 
Twitter for beginners
Twitter for beginnersTwitter for beginners
Twitter for beginners
 
Data and personalization
Data and personalizationData and personalization
Data and personalization
 
A Primer on Text Mining for Business
A Primer on Text Mining for BusinessA Primer on Text Mining for Business
A Primer on Text Mining for Business
 
The business stakes of data integration
The business stakes of data integrationThe business stakes of data integration
The business stakes of data integration
 
What is big data?
What is big data?What is big data?
What is big data?
 
What is "data"?
What is "data"?What is "data"?
What is "data"?
 

Recently uploaded

Dive into Machine Learning Event--MUGDSC
Dive into Machine Learning Event--MUGDSCDive into Machine Learning Event--MUGDSC
Dive into Machine Learning Event--MUGDSCRakshaAgrawal21
 
PEPSICO Presentation to CAGNY Conference Feb 2024
PEPSICO Presentation to CAGNY Conference Feb 2024PEPSICO Presentation to CAGNY Conference Feb 2024
PEPSICO Presentation to CAGNY Conference Feb 2024Neil Kimberley
 
flutter_bootcamp_MUGDSC_Presentation.pptx
flutter_bootcamp_MUGDSC_Presentation.pptxflutter_bootcamp_MUGDSC_Presentation.pptx
flutter_bootcamp_MUGDSC_Presentation.pptxRakshaAgrawal21
 
Session 2 - Value Proposition 1 JAX Bridges
Session 2 - Value Proposition 1 JAX BridgesSession 2 - Value Proposition 1 JAX Bridges
Session 2 - Value Proposition 1 JAX BridgesAnamaria Contreras
 
SlideEgg_300445-Apple Inc(1).pptx case study
SlideEgg_300445-Apple Inc(1).pptx case studySlideEgg_300445-Apple Inc(1).pptx case study
SlideEgg_300445-Apple Inc(1).pptx case studyindobanglatradeinter
 
Bloomerang Fundraising Week02.26.2024.pdf
Bloomerang Fundraising Week02.26.2024.pdfBloomerang Fundraising Week02.26.2024.pdf
Bloomerang Fundraising Week02.26.2024.pdfBloomerang
 
Grevault battery storage system manufacturer
Grevault battery storage system manufacturerGrevault battery storage system manufacturer
Grevault battery storage system manufacturerGrevault
 
PUBLISHING AND LITERARY NETWORKS IN THE SOUTH WEST_EBOOK_WCOVER.pdf
PUBLISHING AND LITERARY NETWORKS IN THE SOUTH WEST_EBOOK_WCOVER.pdfPUBLISHING AND LITERARY NETWORKS IN THE SOUTH WEST_EBOOK_WCOVER.pdf
PUBLISHING AND LITERARY NETWORKS IN THE SOUTH WEST_EBOOK_WCOVER.pdfUniversity of Exeter MA Publishing
 
Leistungsbeschreibung PLM Recruitment 2024
Leistungsbeschreibung PLM Recruitment 2024Leistungsbeschreibung PLM Recruitment 2024
Leistungsbeschreibung PLM Recruitment 2024Joerg Speikamp
 
General Mills Presentation at CAGNY 2024
General Mills Presentation at CAGNY 2024General Mills Presentation at CAGNY 2024
General Mills Presentation at CAGNY 2024Neil Kimberley
 
Research Showcase 2024 final presentation slides
Research Showcase 2024 final presentation slidesResearch Showcase 2024 final presentation slides
Research Showcase 2024 final presentation slidesenterpriseresearchcentre
 
Kraft Heinz Presentation at the 2024 CAGNY.pdf
Kraft Heinz Presentation at the 2024 CAGNY.pdfKraft Heinz Presentation at the 2024 CAGNY.pdf
Kraft Heinz Presentation at the 2024 CAGNY.pdfNeil Kimberley
 
02.22.2024 Email Options in Bloomerang.pdf
02.22.2024 Email Options in Bloomerang.pdf02.22.2024 Email Options in Bloomerang.pdf
02.22.2024 Email Options in Bloomerang.pdfBloomerang
 
Your Expert Guide to CX Orchestration & Enhancing Customer Journeys
Your Expert Guide to CX Orchestration & Enhancing Customer JourneysYour Expert Guide to CX Orchestration & Enhancing Customer Journeys
Your Expert Guide to CX Orchestration & Enhancing Customer JourneysAggregage
 
IT Nation Evolve event 2024 - Quarter 1 - Event
IT Nation Evolve event 2024 - Quarter 1 - EventIT Nation Evolve event 2024 - Quarter 1 - Event
IT Nation Evolve event 2024 - Quarter 1 - EventInbay UK
 
EAPJ Vol VIII February 2024.pdf
EAPJ Vol VIII February 2024.pdfEAPJ Vol VIII February 2024.pdf
EAPJ Vol VIII February 2024.pdfDarryl_Carr
 
Ch 11 Haunted Castle on Hallows Eve.pptx
Ch 11 Haunted Castle on Hallows Eve.pptxCh 11 Haunted Castle on Hallows Eve.pptx
Ch 11 Haunted Castle on Hallows Eve.pptxdeveloperarafat360
 
Cracking the Leadership Shadow Code.pptx
Cracking the Leadership Shadow Code.pptxCracking the Leadership Shadow Code.pptx
Cracking the Leadership Shadow Code.pptxWorkforce Group
 
IPR Collaborators for Change Report: Research on the Relationship Between Com...
IPR Collaborators for Change Report: Research on the Relationship Between Com...IPR Collaborators for Change Report: Research on the Relationship Between Com...
IPR Collaborators for Change Report: Research on the Relationship Between Com...Olivia Kresic
 

Recently uploaded (20)

Dive into Machine Learning Event--MUGDSC
Dive into Machine Learning Event--MUGDSCDive into Machine Learning Event--MUGDSC
Dive into Machine Learning Event--MUGDSC
 
PEPSICO Presentation to CAGNY Conference Feb 2024
PEPSICO Presentation to CAGNY Conference Feb 2024PEPSICO Presentation to CAGNY Conference Feb 2024
PEPSICO Presentation to CAGNY Conference Feb 2024
 
flutter_bootcamp_MUGDSC_Presentation.pptx
flutter_bootcamp_MUGDSC_Presentation.pptxflutter_bootcamp_MUGDSC_Presentation.pptx
flutter_bootcamp_MUGDSC_Presentation.pptx
 
Session 2 - Value Proposition 1 JAX Bridges
Session 2 - Value Proposition 1 JAX BridgesSession 2 - Value Proposition 1 JAX Bridges
Session 2 - Value Proposition 1 JAX Bridges
 
SlideEgg_300445-Apple Inc(1).pptx case study
SlideEgg_300445-Apple Inc(1).pptx case studySlideEgg_300445-Apple Inc(1).pptx case study
SlideEgg_300445-Apple Inc(1).pptx case study
 
Bloomerang Fundraising Week02.26.2024.pdf
Bloomerang Fundraising Week02.26.2024.pdfBloomerang Fundraising Week02.26.2024.pdf
Bloomerang Fundraising Week02.26.2024.pdf
 
Grevault battery storage system manufacturer
Grevault battery storage system manufacturerGrevault battery storage system manufacturer
Grevault battery storage system manufacturer
 
PUBLISHING AND LITERARY NETWORKS IN THE SOUTH WEST_EBOOK_WCOVER.pdf
PUBLISHING AND LITERARY NETWORKS IN THE SOUTH WEST_EBOOK_WCOVER.pdfPUBLISHING AND LITERARY NETWORKS IN THE SOUTH WEST_EBOOK_WCOVER.pdf
PUBLISHING AND LITERARY NETWORKS IN THE SOUTH WEST_EBOOK_WCOVER.pdf
 
Leistungsbeschreibung PLM Recruitment 2024
Leistungsbeschreibung PLM Recruitment 2024Leistungsbeschreibung PLM Recruitment 2024
Leistungsbeschreibung PLM Recruitment 2024
 
General Mills Presentation at CAGNY 2024
General Mills Presentation at CAGNY 2024General Mills Presentation at CAGNY 2024
General Mills Presentation at CAGNY 2024
 
Research Showcase 2024 final presentation slides
Research Showcase 2024 final presentation slidesResearch Showcase 2024 final presentation slides
Research Showcase 2024 final presentation slides
 
Kraft Heinz Presentation at the 2024 CAGNY.pdf
Kraft Heinz Presentation at the 2024 CAGNY.pdfKraft Heinz Presentation at the 2024 CAGNY.pdf
Kraft Heinz Presentation at the 2024 CAGNY.pdf
 
02.22.2024 Email Options in Bloomerang.pdf
02.22.2024 Email Options in Bloomerang.pdf02.22.2024 Email Options in Bloomerang.pdf
02.22.2024 Email Options in Bloomerang.pdf
 
Your Expert Guide to CX Orchestration & Enhancing Customer Journeys
Your Expert Guide to CX Orchestration & Enhancing Customer JourneysYour Expert Guide to CX Orchestration & Enhancing Customer Journeys
Your Expert Guide to CX Orchestration & Enhancing Customer Journeys
 
Master Slideck Research Showcase 2024.pdf
Master Slideck Research Showcase 2024.pdfMaster Slideck Research Showcase 2024.pdf
Master Slideck Research Showcase 2024.pdf
 
IT Nation Evolve event 2024 - Quarter 1 - Event
IT Nation Evolve event 2024 - Quarter 1 - EventIT Nation Evolve event 2024 - Quarter 1 - Event
IT Nation Evolve event 2024 - Quarter 1 - Event
 
EAPJ Vol VIII February 2024.pdf
EAPJ Vol VIII February 2024.pdfEAPJ Vol VIII February 2024.pdf
EAPJ Vol VIII February 2024.pdf
 
Ch 11 Haunted Castle on Hallows Eve.pptx
Ch 11 Haunted Castle on Hallows Eve.pptxCh 11 Haunted Castle on Hallows Eve.pptx
Ch 11 Haunted Castle on Hallows Eve.pptx
 
Cracking the Leadership Shadow Code.pptx
Cracking the Leadership Shadow Code.pptxCracking the Leadership Shadow Code.pptx
Cracking the Leadership Shadow Code.pptx
 
IPR Collaborators for Change Report: Research on the Relationship Between Com...
IPR Collaborators for Change Report: Research on the Relationship Between Com...IPR Collaborators for Change Report: Research on the Relationship Between Com...
IPR Collaborators for Change Report: Research on the Relationship Between Com...
 

An explanation of machine learning for business

  • 1. MK99 – Big Data 1 Big data & cross-platform analytics MOOC lectures Pr. Clement Levallois
  • 2. MK99 – Big Data 2 A short note on machine learning for business
  • 3. MK99 – Big Data 3 Machine Learning • Family of techniques to formulate predictions, based on data •Why is it called Machine learning? –Machine: it is about algorithms running on computers, not equations solved with pen and paper –Learning: the algorithms start with zero accuracy. Then, they get more accurate while being fed with data: the algorithm refines its parameters, it “learns”.
  • 4. MK99 – Big Data 4 Typical set up 1.We start with a training set Data already collected: we know the actual values to be found Ex: a list of consumers, their characteristics and their associated credit score 2.The algorithms are trained on this set -> A series of algorithms run on the training set. Their parameters get adjusted so that the actual values get progressively predicted the most accurately possible. 3.A test set (“fresh data”) is brought -> List of consumer characteristics. Their credit score is known but hidden. 4.Running the trained algo on the test set -> Predict the credit score for each consumer in the test set, using the algorithms that were trained on phase 1 5.A measure of accuracy - Given the correct values to be predicted in the test set, how accurate were the algorithms? -> Where the credit scores accurately predicted? Actual values
  • 5. MK99 – Big Data 5 Vocabulary •Data scientists “train” their model and then test it •They are concerned by “out-of-sample” prediction –The fact that their model predicts accurately data points in the training set (the “sample”) is trivial –This is the accuracy on the test set that matters! –This is called an “out-of-sample” prediction
  • 6. MK99 – Big Data 6 Why is machine learning (ML) so different from statistics? •ML does not focus on causality – just prediction! –Note: for this reason, ML cannot predict the effect of intervention - it has no causal model. •ML has a special concern for out-of-sample prediction –Will be especially careful about over-fitting •ML picks its algorithms from diff academic disciplines –Text, network relations, clustering, not just traditional statistics •Coming from comput. sciences, ML has affinities with big data –Procedures optimized for speed and scale But the best data scientists often started as statisticians / econometricians: See Hal Varian: Chief Economist at Google
  • 7. MK99 – Big Data 7 •Kaggle is a website hosting ML competitions, anybody can join •Goal: make the best prediction on a dataset, with cash prizes •From predicting clicks on ads to epileptic seizures •Always the same setup: a training set, a test set, a scoring based on accuracy.
  • 8. MK99 – Big Data 8 This slide presentation is part of a course offered by EMLYON Business School (www.em-lyon.com) Contact Clement Levallois (levallois [at] em-lyon.com) for more information.