21810762 - BIG DATA AND MACHINE LEARNING

Curriculum

teacher profile | teaching materials

Mutuazione: 21810762 BIG DATA AND MACHINE LEARNING in Relazioni internazionali LM-52 R A - Z CUCINA DOMENICO

Programme

The characteristic of big data- Programming models for big data: Hadoop MapReduce and Apache Spark- Machine Learning algorithms. Apache Spark with R: sparklyr, dplyr, ggplot2.

Core Documentation

Slides provided by the teacher

Jared Dean. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners, 2014, Wiley.

Readings and lecture notes provided by the teacher.

Type of delivery of the course

The course consists of 36 hours divided into lectures and exercises. During the exercises some applications on real data are illustrated.

Attendance

Attendance is not necessary but strongly recommended.

Type of evaluation

The satisfactory achievement of the aims of the course is assessed through an exam with marks out of thirty. The exam includes an oral interview. The mark is expressed out of thirty and the pass mark is 18. The oral interview, of length approximately equal to 25 minutes, consists in theoretical questions on the main methods, models and, in general, notions included in the course program. In particular, the focus will be on evaluating the ability to correctly apply the taught methods, the rigour and clarity of expression.

teacher profile | teaching materials

Mutuazione: 21810762 BIG DATA AND MACHINE LEARNING in Relazioni internazionali LM-52 R A - Z CUCINA DOMENICO

Programme

The characteristic of big data- Programming models for big data: Hadoop MapReduce and Apache Spark- Machine Learning algorithms. Apache Spark with R: sparklyr, dplyr, ggplot2.

Core Documentation

Slides provided by the teacher

Jared Dean. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners, 2014, Wiley.

Readings and lecture notes provided by the teacher.

Type of delivery of the course

The course consists of 36 hours divided into lectures and exercises. During the exercises some applications on real data are illustrated.

Attendance

Attendance is not necessary but strongly recommended.

Type of evaluation

The satisfactory achievement of the aims of the course is assessed through an exam with marks out of thirty. The exam includes an oral interview. The mark is expressed out of thirty and the pass mark is 18. The oral interview, of length approximately equal to 25 minutes, consists in theoretical questions on the main methods, models and, in general, notions included in the course program. In particular, the focus will be on evaluating the ability to correctly apply the taught methods, the rigour and clarity of expression.