amazon – RoboRabbitLabs

The past few years has seen a blur of software giants releasing AI and Machine Learning themed APIs and services. I was, frankly, surprised at how many options there currently are for developers and companies. I think it’s a positive sign for the industry that there are multiple options from reputable brands when it comes to topics like visual and language recognition – these have almost become commodities. You also see strong consolidation into very typical categories like machine learning for building general predictive models, visual recognition, language and speech recognition, conversational bots and news analysis.

Google
- Google Cloud Platform
  - Google Prediction API
    - Hosted Models (Demo)
      - Language Identifier
        
        Spanish, English or French
      - Tag Categoriser
        
        Android, appengine, chrome youtube
      - Sentiment Predictor
        
        Positive or negative label for comments
    - Trained Models
      - Train your own model
  - Google Cloud Vision API
    - Label Detection
    - Explicit Content Detection
    - Logo Detection
    - Landmark Detection
    - Optical Character Recognition
    - Face Detection
    - Image Attributes
  - Cloud Speech API
    - Audio to text
    - >80 languages
    - Streaming Recognition
    - Inappropriate Content Filtering
    - Real-time or Buffered Audio Support
    - Noisy Audio Handling
  - Google Translate API
    - Text Translation
    - Language Detection
- Tensor Flow
  - Open Source graph-based numerical computation and model building

Facebook
- Bot for messenger
  - Ability to build a chat bot for your company that chats via facebook messenger

IBM
- Bluemix
  - Alchemy
    - Alchemy Language
      - Keyword Extraction
      - Entity Extraction
      - Sentiment Analysis
      - Emotion Analysis
      - Concept Tagging
      - Relation Extraction
      - Taxonomy Classification
      - Author Extraction
    - Alchemy Data News
      - News and blog analysis
      - Sentiment, keyword, taxonomy matching
  - Concept Insights
    - Linking concepts between content
  - Dialog
    - Chat interaction
  - Language Translation
  - Natural Language Classifier
    - Phrase classification
  - Personality Insights
    - Social media content analysis to predict personal traits
  - Relationship Extraction
    - Finds relationships between objects and subjects in sentences
  - Retrieve and Rank
    - Detects signals in data
  - Speech To Text, Text to Speech
  - Tone Analyzer
    - Emotion analysis
  - Tradeoff Analytics
    - Decision making support
  - Visual Recognition
  - Cognitive Commerce
    - Support for driving commerce, recommendations etc
  - Cognitive Graph
    - Creates a knowledge graph of data thats typically difficult for a machine to understand
  - Cognitive Insights
    - Personalised commercial insights for commerce

Amazon
- Amazon Machine Learning
  - Managed service to help you model your data with no prior experience
- Amazon Alexa Voice Service
  - Natural language processing

Microsoft
- Microsoft Cognitive Services
  - Vision
    - Categorise images
    - Emotion recognition
    - Facial detection
    - Anaylze video
  - Speech
    - Speech to text, text to speech
    - Speaker recognition
  - Language
    - Spell checking
    - Natural language processing
    - Complex linguistic analysis
    - Text analysis for sentiment, phrases, topics
    - Models trained on web data
  - Knowledge
    - Relationships between academic papers
    - Contextual linking
    - Interactive search
    - Recommendations
  - Search
    - Search
    - Search autosuggest
    - Image and metadata search
    - News search
    - Video search
  - Bot Framework
  - Content Moderator
  - Translator
  - Photo DNA Cloud Service

Did I miss something from this list? Comment and let me know!

Here is a brief summary of Amazon’s machine learning service in AWS.

awsml — AWS ML helping to analyse your data. Slides here

Main function:

Data modelling for prediction using supervised learning
Try to predict characteristics like
- Is this email spam
- Will this customer buy my product

Key benefits:

No infrastructure management required
Democratises data science
- Wizard-based model generation, evaluation and deployment
- Does not require data science expertise
- Built for developers
Bridges the gap between developing a predictive model and building an application

Type of prediction model:

Binary classification using logistic regression
Multiclass classification using multinomial logistic regression
Regression using linear regression

Process:

Determine what question you want to answer
Collect labelled data
Convert to csv format and upload to Amazon S3
Cleanup and aggregate data with AWS ML assistance
Split data into training and aggregation sets using the wizard
Wait for AWS ML to generate a model
Evaluate and modify the model with the wizard
Use the model to create predictions on a batch or single api call basis

Pricing: Pay as you go

Useful links:

Tag: amazon

Update on latest Artificial Intelligence API’s and services

Amazon Machine Learning at a Glance