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AzureDay - What is Machine Learnin?

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?ukasz Grala
?ukasz Grala

AzureDay North 2016. Conference about cloud solutions. What is Machine Learning? Why we need Machine Learning? Where and When we use this? What is Azure Machine Learning and language R. Session introduce to paradigm machine learning, data mining, classes of problems and fundamentals of algorithms. By Data Scientist as a Service.

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AzureDay North Poland Gdynia 2016
What is Machine Learning? ?ukasz Grala | Senior Architect
?ukasz Grala ? Senior architekt rozwi?za┰ Platformy Danych & Business Intelligence & Zaawansowanej Analityki w TIDK ? Tw┏rca ?Data Scientist as as Service￣ ? Certyfikowany trener Microsoft i wyk?adowca na wy?szych uczelniach ? Autor zaawansowanych szkole┰ i warsztat┏w, oraz licznych publikacji i webcast┏w ? Od 2010 roku wyr┏?niany nagrod? Microsoft Data Platform MVP ? Doktorant Politechnika Pozna┰ska C Wydzia? Informatyki (obszar bazy danych, eksploracja danych, uczenie maszynowe) ? Prelegent na licznych konferencjach w kraju i na ?wiecie ? Posiada liczne certyfikaty (MCT, MCSE, MCSA, MCITP,´) ? Cz?onek Polskiego Towarzystwa Informatycznego ? Cz?onek i lider Polish SQL Server User Group (PLSSUG) ? Pasjonat analizy, przechowywania i przetwarzania danych, mi?o?nik Jazzu email lukasz@tidk.pl
Agenda ? Machine Learning ? Machine Learning History ? Class of problem ? Azure Machine Learning ? AML & Excel
Why Machine Learning
History 1763 1805 1812 1913 1950 1951 1967 1982 1995 1997 2016 The Underpinngs of Bayes' Theorem Least Squares Bayes' Theorem Markov Chains First Neural Network Machine Nearest NeighborTuring's Learning Machine Recurrent Neural Network Random Forest Algorithm Support Vector Machines IBM Deep Blue Beats Kasparov 2012 Recognizing Cats on YouTube AlphaGo 1958 Single-layer neural network on a room size computer
Class of Problem ? Estimate product demand ? Predict sales figures ? Analyze marketing returns Regression ? Predict credit risk ? Detect fraud ? Catch abnormal equipments readings Anomaly Detection ? Perform customer segmentation ? Predict customer tastes ? Determine market price Clustering ? Two-Class Classification ? Multi-Class ClassificationClassification
Key Concept C Machine Learning Data Model Parameters Learning Prediction Decision Making Utility Function
Steps to Build Machine Learning Solution
Azure Machine Learning
Algorithm
AzureDay - What is Machine Learnin?
Question? lukasz@tidk.pl

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AzureDay - What is Machine Learnin?

  • 2. What is Machine Learning? ?ukasz Grala | Senior Architect
  • 3. ?ukasz Grala ? Senior architekt rozwi?za┰ Platformy Danych & Business Intelligence & Zaawansowanej Analityki w TIDK ? Tw┏rca ?Data Scientist as as Service￣ ? Certyfikowany trener Microsoft i wyk?adowca na wy?szych uczelniach ? Autor zaawansowanych szkole┰ i warsztat┏w, oraz licznych publikacji i webcast┏w ? Od 2010 roku wyr┏?niany nagrod? Microsoft Data Platform MVP ? Doktorant Politechnika Pozna┰ska C Wydzia? Informatyki (obszar bazy danych, eksploracja danych, uczenie maszynowe) ? Prelegent na licznych konferencjach w kraju i na ?wiecie ? Posiada liczne certyfikaty (MCT, MCSE, MCSA, MCITP,´) ? Cz?onek Polskiego Towarzystwa Informatycznego ? Cz?onek i lider Polish SQL Server User Group (PLSSUG) ? Pasjonat analizy, przechowywania i przetwarzania danych, mi?o?nik Jazzu email lukasz@tidk.pl
  • 4. Agenda ? Machine Learning ? Machine Learning History ? Class of problem ? Azure Machine Learning ? AML & Excel
  • 6. History 1763 1805 1812 1913 1950 1951 1967 1982 1995 1997 2016 The Underpinngs of Bayes' Theorem Least Squares Bayes' Theorem Markov Chains First Neural Network Machine Nearest NeighborTuring's Learning Machine Recurrent Neural Network Random Forest Algorithm Support Vector Machines IBM Deep Blue Beats Kasparov 2012 Recognizing Cats on YouTube AlphaGo 1958 Single-layer neural network on a room size computer
  • 7. Class of Problem ? Estimate product demand ? Predict sales figures ? Analyze marketing returns Regression ? Predict credit risk ? Detect fraud ? Catch abnormal equipments readings Anomaly Detection ? Perform customer segmentation ? Predict customer tastes ? Determine market price Clustering ? Two-Class Classification ? Multi-Class ClassificationClassification
  • 8. Key Concept C Machine Learning Data Model Parameters Learning Prediction Decision Making Utility Function
  • 9. Steps to Build Machine Learning Solution