Szkolenia Micro Focus

Cel szkolenia

kod: VT160-91 | wersja: 9.x

Machine learning is used to discover trends, uncover patterns, peel back layers and detect relationships over large volumes of data. Once put to work, predictive models will identify insights and predict where projects or opportunities will lead. We have incorporated machine learning algorithms into Vertica, enabling in-database prediction-based machine learning over very large data sets and at high speed.

During this course, you will learn:

  • How to prepare your data for model development
  • How to create and evaluate regression, classification, and regression algorithms
  • How to manage existing database models

Upon successful completion of this course, you should be able to:

  • Prepare data for model building
  • Describe the model building and evaluation process
  • Create and evaluate regression, classification, and clustering models
  • Manage the models in your database

Audience/Job Roles

This course is intended for:

  • Novice data analysts who need to understand the how the machine learning algorithms work, and when they are best applied to their data
  • Experienced data scientists who need to know how to use Vertica's built-in machine learning algorithms

Plan szkolenia Rozwiń listę

  1. Introduction to Machine Learning
    • Describe the principles of machine learning
    • Describe the advantages of machine learning
  2. Data Preparation
    • Describe the data preparation process
    • Prepare data using the following functions:
      • Normalize data scales
      • Impute missing values
      • Identify and remove outlying values
      • Smooth class representation within a column
      • Create training and testing data sets
  3. Regression Algorithms
    • Build and evaluate the following model types:
      • Linear regression
      • Random forest
      • Support vector machines
  4. Classification Algorithms
    • Build and evaluate the following model types:
      • Logistic regression
      • Random forest
      • Support vector machines
      • Naïve Bayes
  5. Clustering Algorithms
    • Build and evaluate the following model types:
      • K-means
  6. Model Management
    • Review existing models and their attributes
    • Alter name, schema, and ownership of a model
    • Remove a model from the database
    • Move models between databases
Pobierz konspekt szkolenia w formacie PDF

Dodatkowe informacje

Wymagania wstępne

To be successful in this course, you should have the following prerequisites or knowledge:

  • Intermediate knowledge of RDBMS concepts (understanding databases and schemas, database normalization, etc.)
  • Basic understanding of SQL (familiarity with basic SQL syntax, ability to troubleshoot syntax errors, etc.)
  • Familiarity with machine learning principles
Poziom trudności
Czas trwania 1 dzień

The participants will obtain certificates signed by Micro Focus (course completion).


Authorized Micro Focus Trainer.

Pozostałe szkolenia Micro Focus | Vertica & IDOL

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