General document Image Recognition.
Final presentation Image Recognition.
Resume Document
Warnings: There are some attempts at humor here.
Augmented Reality / Image Recognition
Moodstocks
Augmented Reality / Image Recognition
- Image caption
- Secuence classfication
- Translation
- Named entity recognition
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- Bluemix IBM
- Moodstocks
- Vuforia
- Wikitude
- Wazzat Labs
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Demo Bluemix IBM!
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Flow of the service
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Use cases
- Manufacturing: Use images from a manufacturing setting to make sure products are being positioned correctly on an assembly line
- Visual Auditing: Look for visual compliance or deterioration in a fleet of trucks, planes, or windmills out in the field, train custom classifiers to understand what defects look like
- Insurance: Rapidly process claims by using images to classify claims into different categories.
- Social listening: Use images from your product line or your logo to track buzz about your company on social media
- Social commerce: Use an image of a plated dish to find out which restaurant serves it and find reviews, use a travel photo to find vacation suggestions based on similar experiences, use a house image to find similar homes that are for sale
- Retail: Take a photo of a favorite outfit to find stores with those clothes in stock or on sale, use a travel image to find retail suggestions in that area
- Education: Create image-based applications to educate about taxonomies, use pictures to find educational material on similar subjects
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Demo Bluemix IBM
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Demo Bluemix IBM
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Demo Bluemix IBM
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Demo Bluemix IBM !!!!!
IBM Watson Services
- AlchemyLanguage
- AlchemyVision
- AlchemyData News
- Authorization
- Concept Insights
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IBM Watson Services
- Conversation
- Dialog
- Document Conversion
- Language Translator
- Natural Language Classifier
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IBM Watson Services
- Personality Insights
- Relationship Extraction
- Retrieve and Rank
- Speech to Text
- Text to Speech
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IBM Watson Services
- Tone Analyzer
- Tradeoff Analytics
- Visual Insights
- Visual Recognition
ConvNetJS Deep Q Learning Demo
This demo follows the description of the Deep Q Learning algorithm described in Playing Atari with Deep Reinforcement Learning, a paper from NIPS 2013 Deep Learning Workshop from DeepMind. The paper is a nice demo of a fairly standard (model-free) Reinforcement Learning algorithm (Q Learning) learning to play Atari games.
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<iframe frameborder=0 width=”900” height=”700” marginheight=0 marginwidth=0 scrolling=”auto” src=”http://www.pepitosoft.com/demos/rldemo/index.html”></iframe>
Useful, Reference and Future links
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Useful, Reference and Future links
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Useful, Reference and Future links
- convnetjs
- THE MNIST DATABASE
- Neural Networks in Javascript
- Top Machine Learning Libraries for Javascript
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Useful, Reference and Future links
- Playing Atari with Deep Reinforcement Learning
- Understanding LSTM Networks
- 5 Machine Learning Projects You Can No Longer Overlook
- Top 10 Machine Learning Projects on Github
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Useful, Reference and Future links
- Lian Li: Machine Learning with Node.js - JSUnconf 2016
- Machine learning is not the future - Google I/O 2016
- Machine Learning Tutorial for JavaScript Hackers: Tips On Gathering and Pre-Processing Data
- ConvNetJS – Deep Learning in your browser
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Useful, Reference and Future links
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Useful, Reference and Future links
- IBM Watson: Using the Visual Recognition service
- Neural Networks in JavaScript
- Introduction to Artificial Neural Networks
- A ‘Brief’ History of Neural Nets and Deep Learning
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Useful, Reference and Future links
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Useful, Reference and Future links
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