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sesiuni:data_science [2016/05/30 18:24] dserban [Topics] |
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| == When and Where? == | == When and Where? == | ||
| - | * **Between**: 25 June 2016 - 31 August 2016 (every Saturday and Sunday) | + | **Between**: 3-25 September 2016 (every Saturday and Sunday, and the actual workshop dates are 3, 4, 10, 11, 17, 18, 24, 25) |
| - | Private communications will be sent to announce further details after registration is complete and the list of participants is finalized. | + | Private communications will be sent to the selected participants to announce further details (after registration is complete and the list of participants is finalized). |
| == Topics == | == Topics == | ||
| Line 20: | Line 20: | ||
| * Working in the PySpark shell | * Working in the PySpark shell | ||
| * Working with PySpark in an iPython notebook | * Working with PySpark in an iPython notebook | ||
| + | * Building Spark/Scala Applications with sbt | ||
| * Standalone Applications | * Standalone Applications | ||
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| * The DataFrame API | * The DataFrame API | ||
| * Inner Joins and Left Outer Joins in the RDD API versus in Spark SQL | * Inner Joins and Left Outer Joins in the RDD API versus in Spark SQL | ||
| + | * Datasets (compile-time type-safe DataFrames) | ||
| Building Interactive Data Analytics Apps With Flask and Spark | Building Interactive Data Analytics Apps With Flask and Spark | ||
| Line 56: | Line 58: | ||
| * A Simple Example - Stream of Integers / Rolling Sum | * A Simple Example - Stream of Integers / Rolling Sum | ||
| - | * Streaming data via TCP socket (netcat) | + | * Streaming Data via TCP socket (netcat) |
| - | * Streaming data via Kafka topic (Apache Kafka) | + | * Streaming Data via Kafka topic (Apache Kafka) |
| - | * Aggregating streams and storing the results in a NoSQL datastore (Apache Cassandra) | + | * Storing Streaming Analytics Results in a NoSQL Datastore (Apache Cassandra) |
| + | * Structured Streaming / Infinite DataFrames | ||
| Advanced Spark Programming | Advanced Spark Programming | ||
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| * Overview and Terminology | * Overview and Terminology | ||
| - | * Machine Learning Basics. What is a Feature | + | * Machine Learning Basics |
| - | * The LabeledPoint Data Type | + | |
| * TF-IDF | * TF-IDF | ||
| * Preparing The Data For Analysis / Stemming, Stopword Elimination | * Preparing The Data For Analysis / Stemming, Stopword Elimination | ||
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| You can register for the workshop using the [[https://docs.google.com/forms/d/1ocS-KDKF99HWILR5LaEV8KE-38xa0kltZoFu8sKWjI8/viewform|online registration form]]. | You can register for the workshop using the [[https://docs.google.com/forms/d/1ocS-KDKF99HWILR5LaEV8KE-38xa0kltZoFu8sKWjI8/viewform|online registration form]]. | ||
| + | |||
| + | Deadline: September 2nd, 23:59. | ||
| If you have any questions, please ask them [[https://github.com/dserban/datascience2016summer/issues/1|here]]. | If you have any questions, please ask them [[https://github.com/dserban/datascience2016summer/issues/1|here]]. | ||