IoT Evolution EXPO: Machine Learning Introductory Certification. PART 1
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Transcript of IoT Evolution EXPO: Machine Learning Introductory Certification. PART 1
Adj. Prof. Giuseppe Mascarella – Brief Bio
• Contact us for 1 free consultation: [email protected]
• Twitter: @giuseppeHighTec• Linkedin: www.linkedin.com/in/giuseppemascarella
Related ML Sessions
• Thursday 5:30 -Expo Hall TheatreBirds of a Feather: Apache Spark, Fast and Furious IoT
• Friday 9 AM (Grand D)Machine Learning and the Cloud - BIML-08
IoT IT - BI and Machine
• Friday 11:00 Grand CConnected Building and Cities IoT and Sustainable Resources-CB-09
• ML at AizoOn Booth 2003
Tuesday Feb 7th
1.Machine Learning Intro: New Rules (1:30 PM)
2. Machine Learning Impact on IoT (2:15 PM)
3. Machine Learning IoT ROI (3:15 PM)
Machine Learning Intro: New Rules (1:30)1.What is it that Machines are
learning? 2. How intelligence is being packed
into the ML for IoT? 3. This is an overview of what Machine
Learning is and does with IoT
What is Changing?
Source: www.microsoft.com
Data is out there and is free (Open data). It provides no competitive advantages. Finding patterns in data is the holy grail (the oil in a barrel!)
What is Changing?
ML is Not Only for Data Patterns and Forecasts
It’s interface is based on ‘machine learning’ i.e. it learns and becomes better with use. This will be common with ALL products and will determine the competitive advantage of companies. Its a winner takes all game! Every product will have a ‘self learning’ interface/component and the product which learns best will win!
1. What Is Machine Learning?With 30 billion ( sense and Kinetic) not static by 2020
Gartner, the Internet of Things (IoT) is a network with the aim to connect physical objects that contain embedded technology to communicate, sense or interact with their internal states or the external environment.
Machine learning is defined as the ability of a machine to vary the outcome of a situation or behavior based on knowledge or observation which is essential for IoT solutions.
2. How intelligence is being packed into the ML for IoT?
2. Directed Knowledge where knowledge created elsewhere (by a central authority) will be used to modify edge behavior
1. Observed Knowledge which will modify behavior based on local learning (context)
3. Sensor Fusion Knowledge the combining of sensory data and data delivery orchestration such that the resulting information is in some sense better than would be possible when these sources were used individually. See Kalman filter
Think about this like how the human brain learns from life experiences vs. from explicit instructions.The more data, the more effective the learning is.
Machine Learning is a branch of Computer Science that, instead of applying pre-defined logic to solve problems in explicit, imperative logic, applies data science algorithms to discover patterns implicit in the data.
Machine Learning
Microsoft Internal Applications Benchmark
Machine Intelligence Functional Components
Prof. Kris Hammond, Northwestern University http://ai.xprize.org/news/periodic-table-of-ai?imm_mid=0ec3b7&cmp=em-data-na-na-newsltr_ai_20170116
Techiniques
http://docs.h2o.ai/h2o/latest-stable/index.html
Machine Intelligence AlgorithmsModelling Techniques
Supervised Learning1. Classification2. Regression3. Anomaly Detection (Find The Unusual)4. etc
UN-Supervised Learning1. Clustering K-Means 2. Anomaly Det. Principal Components
Analysis (PCA)3. etc
LanguagesR, Python, Java, Scala
Algorithms
• GLM• Bayesian• Random Forest• Neural Network• Etc…
• Classification
• RegressionY = mx+n
ML Algorithms
ML Algorithms
Machine Learning Intro: New Rules (1:30)1. What is it that Machines are
learning? 2. How intelligence is being packed
into the ML for IoT? 3. This is an overview of what Machine
Learning is and does with IoT
Related ML Sessions
• Thursday 5:30 -Expo Hall TheatreBirds of a Feather: Apache Spark, Fast and Furious IoT
• Friday 9 AM (Grand D)Machine Learning and the Cloud - BIML-08
IoT IT - BI and Machine
• Friday 11:00 Grand CConnected Building and Cities IoT and Sustainable Resources-CB-09
• ML at AizoOn Booth 2003
Tuesday Feb 7th
1.Machine Learning Intro: New Rules (1:30 PM)
2. Machine Learning Impact on IoT (2:15 PM)
3. Machine Learning IoT ROI (3:15 PM)
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