Struttura del corso
Spark.mllib: tipi di dati, algoritmi e utilità
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Tipi di dati
Statistiche di base
Statistiche di riepilogo
Correlazioni
campionamento stratificato
verifica delle ipotesi
Test di significatività dello streaming
Generazione di dati casuali
Requisiti
Conoscenza di uno dei seguenti argomenti:
- Giava
- Scala
- pitone
- SparkR.
Recensioni (8)
This is one of the best hands-on with exercises programming courses I have ever taken.
Laura Kahn
Corso - Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP
The VM I liked very much The Teacher was very knowledgeable regarding the topic as well as other topics, he was very nice and friendly I liked the facility in Dubai.
Safar Alqahtani - Elm Information Security
Corso - Big Data Analytics in Health
Sufficient hands on, trainer is knowledgable
Chris Tan
Corso - A Practical Introduction to Stream Processing
very interactive...
Richard Langford
Corso - SMACK Stack for Data Science
Impegno e disponibilità a spiegare argomenti collaterali.
Marek - Krajowy Rejestr Długów Biuro Informacji Gospodarczej S.A.
Corso - Apache Spark Fundamentals
Traduzione automatica
Having hands on session / assignments
Poornima Chenthamarakshan - Intelligent Medical Objects
Corso - Apache Spark in the Cloud
Esercitazioni e scambi durante domande e risposte
Antoine - Physiobotic
Corso - Scaling Data Pipelines with Spark NLP
Traduzione automatica
The fact that we were able to take with us most of the information/course/presentation/exercises done, so that we can look over them and perhaps redo what we didint understand first time or improve what we already did.