Machine Learning with H2O Flow

4.8
96 個評分
提供方
Coursera Project Network
3,800 人已註冊
在此指導項目中,您將:

Train and evaluate machine learning models with H2O Flow

Solve a business analytics problem using machine learning with Flow and AutoML

Clock1.2 hours
Intermediate中級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

This is a hands-on, guided introduction to using H2O Flow for machine learning. By the end of this project, you will be able to train and evaluate machine learning models with H2O Flow and AutoML, without writing a single line of code! You will use the point and click, web-based interface to H2O called Flow to solve a business analytics problem with machine learning. H2O is a leading open-source machine learning and artificial intelligence platform trusted by data scientists and machine learning practitioners. It has APIs available in R, Python, Scala, and also a web-based point and click interface called Flow. 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 pipelines such as data pre-processing, feature engineering, and model deployment. To get the most out of this project, we recommend that you have an understanding of basic machine learning theory, and have trained machine learning models. 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.

您要培養的技能

data-scienceautomlbusiness-analyticsmachine-learningH2O

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  1. Introduction and Project Overview

  2. Importing and Parsing Data

  3. Creating Training and Test Splits

  4. Build and Evaluate a GLM

  5. Run H2O AutoML with Flow

  6. View Leaderboard and Model Exploration

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

審閱

來自MACHINE LEARNING WITH H2O FLOW的熱門評論

查看所有評論

常見問題

常見問題

還有其他問題嗎?請訪問 學生幫助中心