Machine Learning using Spark

Lucian Neghina
Machine Learning using Spark

Acest curs este predat în limba română, iar materialele sunt în limba engleză şi/sau în limba română, după caz.

La cerere, cursul poate fi personalizat.

Learn how to use the latest Apache Spark for machine learning on big data.

Using: Apache Spark 2.1, Apache Zeppelin
Prerequisites: IDE (Eclipse, IDEA)
Useful: Scala, functional programming, mathematics, statistics

Caracteristici curs

  • Capitole 22
  • Durata 3 Zile
  • Nivel de cunostinte Orice nivel
  • Limba Romana
  • Studenti 12
  • Ziua 1

    • Capitol 1.1 Spark and Kafka in the Big-Data Context Locked 0m
    • Capitol 1.2 Introduction to Apache Spark Locked 0m
    • Capitol 1.3 Interacting with Spark Locked 0m
    • Capitol 1.4 Programming with RDDs Locked 0m
    • Capitol 1.5 Working with Key-Value Pairs Locked 0m
    • Capitol 1.6 Simple Applications using Spark Locked 0m
  • Ziua 2

    • Capitol 2.1 Spark DataFrames/Datasets Locked 0m
    • Capitol 2.2 Spark SQL Locked 0m
    • Capitol 2.3 Machine learning basics Locked 0m
    • Capitol 2.4 Overview of Spark MLlib & ML Locked 0m
  • Ziua 3

    • Capitol 3.1 Details about Spark MLlib Locked 0m
    • Capitol 3.2 Performing linear algebra Locked 0m
    • Capitol 3.3 Scaling and normalizing features Locked 0m
    • Capitol 3.4 Training and applying a linear regression model Locked 0m
    • Capitol 3.5 Evaluating the model’s performance Locked 0m
    • Capitol 3.6 Using regularization Locked 0m
    • Capitol 3.7 Optimizing linear regression Locked 0m
    • Capitol 3.8 Recommendation Engines Locked 0m
    • Capitol 3.9 Details about Spark ML Locked 0m
    • Capitol 3.10 Logistic regression Locked 0m
    • Capitol 3.11 Decision trees & Random forests Locked 0m
    • Capitol 3.12 K-means clustering Locked 0m
Lucian Neghina
Big Data Architect