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NodeMN: Building AI into your Node.js apps
- 2. Observable and unobservable Variables !Data usually comes from a process that is not completely known. !We model this as a random process and analyze it using probability theory. !Example: !Tossing a coin is a random process, as we cannot predict at any toss on which side the coin will land. Heads or tails? !We can only talk about the probability of the outcome (observable variable) for the next toss. !(In case we would have all the information (e.g. speed of throw, angle, wind, etc.) we might be able to precisely predict outcome. These variables are unobservable variables.) 42 Naive Bayes !Suppose I want to know if a news article is about sports, politics, entertainment. !Classes: sports, politics, entertainment !Probability that a document d belongs to class c !Probability of class c given document d meeting hello P(c|d) = P(c)P(d|c) P(d) ation for text categorization e (can do surprisingly well) .. spam 51 Source: Kenji Sagae Guest Lecture in CSCI 599 (Fall 2014) Spam meeting hello bank click Naïve Bayes:
- 3. Building AI into your Node.js apps DAVID WASHINGTON DIRECTOR MICROSOFT DWASHIN@MICROSOFT.COM
- 5. ` INTEL MICROSOFT CRM WINDOWS DEVELOPER EXPERIENCE PENTIUM4 INDUSTRIAL DEVELOPER FAB12 FAB22 ARIZONA V1 V1.2 V3 QUOTES ORDERS INVOICES LONGHORN SOFTWARE DEVELOPER ENGINEER SHELL TEAM DESKTOP OPEN SAVE EXPLORER BRIEFCASE SEATTLE WINDOWS 7 PROGRAM MANAGER SHELL TEAM SEARCH FILE API OPEN SAVE ADOBE APPLE FILE COPY PDC2008 WINDOWS 8 PROGRAM MANAGER LEAD SHELL TEAM USER EXPREINCE WINDOWS EXPLORER HIGH DPI TOUCH KEYBOARD SURFACE TOUCH COVER LANGUAGE MODEL TECHNICAL EVANGELISM DIRECTOR CENTRAL US DWCARES.COM GAMEDEV MHACKS TECHCRUNCH DISRUPT HACKTX HACKILLINOIS IOT JAVASCRIPT MINNEAPOLIS SOFTWARE DEVELOPER ENGINEER INTERN FULL-TIME SEATTLE UNIVERSITY OF WISCONSIN COMPUTER ENGINEERING GRADUATE 2004
- 6. What is Artificial Intelligence? “The exciting new effort to make computers thinks … machine with minds, in the full and literal sense” (Haugeland 1985) “The study of mental faculties through the use of computational models” (Charniak et al. 1985) “The art of creating machines that perform functions that require intelligence when performed by people” (Kurzweil, 1990) “A field of study that seeks to explain and emulate intelligent behavior in terms of computational processes” (Schalkol, 1990) “The scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines.” (AAAI)
- 8. Intelligence APIs Vision Computer vision API, Emotion API, Face API, Video API Speech Custom recognition intelligence service (CRIS), Speaker recognition API, Speech to Text API, Text to Speech API Language Language understanding intelligence service (LUIS), Linguistic analytics API, Bing spell check API, Text analytics API, Web language model API Knowledge Academic knowledge API, Entity linking intelligence service, Knowledge exploration service, Recommendations API Search Bing web search API, Bing image search API, Bing news search API, Bing video search API, Bing autosuggest API
- 9. Vision
- 12. Speech
- 13. Language
Notas do Editor
- Supervised Machine Learning Given a labelled data set, we already know what our correct output should look like We can use this to find relationships and predict results of new data
- Supervised Machine Learning Given a labelled data set, we already know what our correct output should look like We can use this to find relationships and predict results of new data
- Engineering for a Billion People Building a high-quality operating system is hard, and it’s even harder when you have a sixth of the planet using your product in thousands of different ways. In this session, David Washington, Director of Developer Experience at Microsoft, will walk though his experience as an engineer designing and building Windows 7 and Windows 8. He’ll show you what goes on behind the scenes on a large-scale engineering project and you’ll see unreleased prototypes and architecture explorations for how a feature comes about. David Washington, a 2004 UW-Madison Computer Engineering graduate, spent nine years designing and engineering Windows. He’s led the teams that built file copy and the Windows Explorer, the end-to-end experience for how Windows 8 scales and adapts responsively across all screens sizes, and the touch keyboard and it’s adaptive language model. Currently he is the Director of Developer Evangelism, where his works to inspire and enable startups, students and independent app developers around the major cities in the Central United States.
- Think like humans -> think rationally Act like humans -> act rationally
- Think like humans -> think rationally Act like humans -> act rationally
- https://github.com/SharePointing/Azure.Intelligence
- Microsoft Cognitive Services --- Many intelligent APIs are collected all in one place. An in-browser interactive visual console lets you easily test or preview APIs before you sign up for access keys. APIs have a free tier for users with a small number of monthly transactions.
- https://github.com/Microsoft/Cognitive-LUIS-Node.js
- https://github.com/Microsoft/Cognitive-LUIS-Node.js