Spotlight on Emerging Data Science Worskspaces and Spark as Development Levers
summary
Demonstrates building ML apps with Apache Spark, a cloud Data Science Experience notebook and Watson Machine Learning to train Spark ML models, create a GUI pipeline, and one‑click deploy a REST scoring endpoint. Shows Jupyter notebooks (Python, TensorFlow style‑transfer demo), automatic Spark cluster provisioning, free individual tier and 30‑day trial, and an example model that returns about 58% accuracy on the demo dataset and a live prediction at ~68% for a sample input.
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chapters (19)
- 0:00Start
- 2:20Data Driven Organizations-Data Science is a Team Sport
- 4:13What is a Data Scientist?
- 5:48Known Data Science Platforms Gartner February 2017 Magic Quadrant
- 6:47Google Trends, Open Source Data Science Technologies
- 7:47Open Source - Data Science Ecosystem
- 9:53What is Apache Spark?
- 11:00Apache Spark is Hot!
- 11:22Apache Spark does more, with less...
- 12:21Apache Spark Architecture
- 17:28Apache Spark works with Open Source Notebooks...
- 18:12Apache Spark Languages
- 19:10Apache Spark Library Usage
- 19:40IBM-Investing in Apache Spark
- 20:43IBM Contributions to Apache Spark
- 22:47Apache Spark Accelerating Machine Learning
- 23:41What is Machine Learning?
- 24:19Process to create a Machine Learning Model
- 26:10IBM's Mission
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