Predictive Analytics for Business with H2O in R

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In diesem Angeleitetes Projekt werden Sie:

Apply machine learning and predictive analytics to solve a business problem

Explain and describe automatic machine learning (AutoML)

Perform Automatic Machine Learning with H2O and R

Clock1.5 hours
IntermediateMittel
CloudKein Download erforderlich
VideoVideo auf geteiltem Bildschirm
Comment DotsEnglisch
LaptopNur Desktop

This is a hands-on, guided project on Predictive Analytics for Business with H2O in R. By the end of this project, you will be able apply machine learning and predictive analytics to solve a business problem, explain and describe automatic machine learning, perform automatic machine learning (AutoML) with H2O in R. We will take a data-driven approach to predict the success of bank telemarketing. H2O's AutoML automates the process of training and tuning a large selection of models, allowing the user to focus on other aspects of the data science and machine learning pipeline such as data pre-processing, feature engineering and model deployment. To successfully complete the project, we recommend that you have prior experience with programming in R, basic machine learning theory, and have trained ML models in R. We will not be exploring how any particular model works nor dive into the math behind them. Instead, we assume you have this foundational knowledge and want to learn to use H2O in R for predictive analytics. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Kompetenzen, die Sie erwerben werden

predictive-analyticsr-programming-languagebusiness-analyticsmachine-learningH2O

Schritt für Schritt lernen

In einem Video, das auf einer Hälfte Ihres Arbeitsbereichs abgespielt wird, führt Sie Ihr Dozent durch diese Schritte:

  1. Introduction and Project Overview

  2. Getting to Know the Marketing Data

  3. Load the Data into R

  4. Data Prep & Start H2O Cluster

  5. Run H2O AutoML

  6. AutoML Leaderboard and Ensemble Exploration

Ablauf angeleiteter Projekte

Ihr Arbeitsbereich ist ein Cloud-Desktop direkt in Ihrem Browser, kein Download erforderlich

Ihr Dozent leitet Sie in einem Video mit geteiltem Bildschirm Schritt für Schritt an.

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