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Machine Learning in the Cloud

Machine Learning in the Cloud

Aug 4th 2017 - LGBTech Event Amsterdam @ Google

Lee Boonstra

August 08, 2017

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  1. Confidential + Proprietary Confidential + Proprietary Lee Boonstra - Customer

    Engineer, Google Cloud Machine Learning in the Cloud
  2. Current GCP Region Edge points of presence Data centers across

    the world Singapore S Carolina N Virginia London Tokyo Taiwan Mumbai Sydney Oregon Iowa São Paulo Finland Belgium Frankfurt 2017 GCP Region Fastest, most reliable network
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  4. It’s easier to make computers learn than to build smarter

    computers Machine Learning Process of making computers learn Artificial Intelligence Process of building smarter computers
  5. Why Google? Tensorflow is what we use for our own

    internal machine learning projects, and now it’s available to you! Google made it open source. • More than 480 contributions • 10,000 commits in a year • 53k star rating Tutorials to get started at https://www.tensorflow.org
  6. Two ways we can help you benefit from ML Use

    your own data to train models Ready to use Machine Learning models Cloud Vision API Cloud Translation API Cloud Natural Language API Cloud Speech API Cloud Machine Learning Engine TensorFlow Cloud Jobs API Cloud Video Inelligence
  7. Vision API Detect broad sets of categories within an image,

    ranging from modes of transportation to animals. Analyze facial features to detect emotions: joy, sorrow, anger. Detect logos. Detect and extract text within an image, with support for a broad range of languages, along with support for automatic language identification. Extract text Detect different types of inappropriate content from adult to violent content. Powered by Google Safe Search Detect inappropriate content Object Recognition Facial sentiment & logos
  8. Speech API Powered by deep learning neural networking to power

    your applications.. No need for signal processing or noise cancellation before calling API. Can handle noisy audio from a variety of environments. Noise Robustness Can provide context hints for improved accuracy. Especially useful for device and app use cases. Word Hints Speech Recognition Recognizes over 80 languages & variants. Can also filter inappropriate content in text results Over 80 languages Can stream text results, returning partial recognition results as they become available. Can also be run on buffered or archived audio files. Real-time results
  9. Natural Language API Identify entities and label by types such

    as person, organization, location, events, products and media. Enables you to easily analyze text in multiple languages including English, Spanish and Japanese. Extract tokens and sentences, identify parts of speech (PoS) and create dependency parse trees for each sentence. Syntax analysis Entity Recognition Multi-Language Support Understand the overall sentiment expressed in a block of text. Sentiment Analysis
  10. Translation API Supports more than 100 languages and thousands of

    language pairs. Behind the scenes, Translation API is learning from logs analysis and human translation examples. Existing language pairs improve and new language pairs come online at no additional cost. Sometimes you don’t know your source text language in advance. Can automatically identify languages with high accuracy. Automatic language detection The Premium edition is tailored for users who need precise, long-form translation services (e.g. livestream translations, high volume of emails, detailed articles and documents) Premium edition BETA Text Translation Continuous Updates
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  12. BETA: Video Intelligence API Detect entities within the video, such

    as "dog", "flower" or "car". You can now search your video catalog the same way you search text documents.. Extract actionable insights from video files without requiring any machine learning or computer vision knowledge. Enable Video Search More features will be added to the Video Intelligence API during the BETA period. More to come ... BETA Label Detection Insights From Videos