Jazoon Zurich Autumn 2017
| title | author | length |
|---|---|---|
| Build your intelligent enterprise with SAP machine learning | Christian Michel | 27m |
SAP Leonardo Machine Learning Foundation on SAP Cloud Platform provides ready REST services for text analytics, image-based analytics and service ticket… | ||
| Applied AI: Real-world use cases for Microsoft's Azure Cognitive Services | Paige Bailey | 33m |
Shows a concrete Jabil circuit-board pipeline: use Project Pendleton for automated data cleaning, train on a deep learning VM with GPU via the Azure Machine… | ||
| Run Deep Learning models in the browser with JavaScript and ConvNetJS | Christoph Körner | 39m |
Browser-based inference and even training run end-to-end using JavaScript: models exported from Caffe/Keras load into ConvNetJS-style runtimes, use typed… | ||
| Enterprise Chatbots (using messaging and AI to build novel user interfaces for work) | Mike Brevoort | 55m |
Argues chatbots aren’t the end goal but that messaging platforms become workflow surfaces, built on Slack APIs (postMessage, buttons, forms) and enriched with… | ||
| JVM based DeepLearing on IoT data with Apache Spark | Romeo Kienzler | 35m |
Shows a runnable pipeline that trains an LSTM autoencoder on IoT sensor streams using DeepLearning4J on Apache Spark, running distributed on CPU/GPU clusters… | ||
| Apache Spark and ML workflows | Juliet Hougland | 44m |
Shows how to train churn models from a telco CSV using Spark MLlib pipelines (string indexer, one‑hot encoding, VectorAssembler) and how to export/apply models… | ||
| Anatomy of an open source voice assistant | Åke Forslund | 43m |
Mycroft presents an open source voice assistant stack: a Mark 1 Raspberry Pi enclosure with a wake word that currently false-triggers, a cloud STT pipeline and… | ||
| nothing matches | ||