madeklion.blogg.se - Rapidminer studio tutorial

#RAPIDMINER STUDIO TUTORIAL HOW TO#
#RAPIDMINER STUDIO TUTORIAL INSTALL#
#RAPIDMINER STUDIO TUTORIAL SERIES#
#RAPIDMINER STUDIO TUTORIAL DOWNLOAD#
#RAPIDMINER STUDIO TUTORIAL FREE#

RapidMiner Tutorial: Auto Model Tutorial and Video.

RapidMiner processes for Regression regression.

RapidMiner processes for Classification classification, example, evaluation, compare classifiers.

RapidMiner processes for Clustering k-means, hierarchical, example.

Slides: Data Mining - Predictive Analytics ( Machine Learning Videos from StatQuest).

Purpose: Understand the basic supervised and unsupervised learning techniques used in data science.

Predictive Analytics: Data Mining/Machine Learning

Regular expressions for text manipultaion: Intro video to regular expressions in RapidMinder and a general introduction to regular expressions.Ħ.

Videos: Get Started with RapidMiner & Machine Learning.

Tutorial: Getting started with RapidMiner.

RapidMiner process Basic statistics and visualization (save and import process in rapidminer).

#RAPIDMINER STUDIO TUTORIAL DOWNLOAD#

You will need to download and add the census dataset. rmp file and import process in rapidminer).

RapidMiner process Cleaning and preprocessing data (save the.

Introduction to Descriptive Statistics ( Statistics videos from StatQuest).

#RAPIDMINER STUDIO TUTORIAL FREE#

Tools: Excel, RapidMiner Studio (you have to sign up for a free account and may apply for a free educational license).

Purpose: Learn about the scales of measurement, histograms, distributions, random samples, mean, variance, and proportions.

Descriptive Analytics: Data, Distributions and Correlation

SQLite Tutorial (start with SELECT Query in the menu to the left)ĥ.

Quizzes to check your SQL knowledge: Quiz 1, Quiz 2, Quiz 3.

Examples from class: Product Database (SQLite save and open with DB Browser), Example Queries, Cross Products and Joins.

Not covered in class: Entity-Relationship Model.

Tools: DB Browser for SQLite (install the latest version).

We will talk about database design, importing data, simple SQL queries, joins, and aggregation.

Purpose: Relational databases are the most used way to store, manage and manipulate data.

A Visual History of Which Countries Have Dominated the Summer Olympics (NY Times, 2016).

Beauty of Visualization (TEDGlobal, 2010).

How Do You Tell A Story With Data Visualization? (Forbes, 2019).

Case Study: Using Excel to create a map visualization of the GDP by US state.

#RAPIDMINER STUDIO TUTORIAL SERIES#

Case Study: Using Excel trendlines to predict M2 Money supply time series data.

Example: 4 questions about weather-driven power outages, answered.

The Best and Worst Data Visualizations of 2018 (KDNuggets, 2019).

A beginner’s guide to identifying misleading data visualizations.

#RAPIDMINER STUDIO TUTORIAL HOW TO#

Data Visualization 101: How to Choose the Right Chart or Graph for Your Data.Watch on your own: The best stats you’ve ever seen (Hans Rosling’s TED talk, 2006).Purpose: Learn basic visualization skills (scatter plot, bar charts,histogramms and line charts wih trend lines).Excel for Data Analysis Tutorial (Read: Importing data, cleaning data with text function, tables, conditional formatting, sorting, and filtering).Excel Tutorial (Basics, Editing Worksheets, Formatting Cells, and Working with Formulas.Finished workbook examples: Cleaned MLB data, workbook with slicers, pivot table and visualizations.Data: MLB Heights and Weights, MLB Player Statistics.Instructions: Analyzing MLB Player Data (Tables in Excel).Things to know about Pivot tables in Excel.Things to know about Excel Tables (optional: Using structured references with Excel tables).If you need to brush up on basic Excel skills, then go through the reference material below.

#RAPIDMINER STUDIO TUTORIAL INSTALL#

Tools: Excel (install the latest version from SMU Office 365 download - use install Office link).We will learn about importing data, cleaning, formatting, functions, and pivot tables. Purpose: Tables are the most basic form of organizing data.

How to find and delete the data Google collects about you (CNET).Template: Data Science Report Template (Word).Watch: Big data is better data (TED talk, 2014).Purpose: Introduction to the course and the data science process including applications and ethics.The reading material will be part of the exam. Note: Readings need to be done before class at home. Tools presented in this course include SQL, Excel, along with other state-of-the-art tools. The fundamental practical skills necessary will be taught in class, and each step will be illustrated with small examples. The course will introduce data-centric thinking including a discussion of how data is acquired, managed, manipulated, visualized, and used to support problem-solving. This course provides a first introduction to the exciting field of data science using applications and case studies from various domains (e.g., social media, marketing, sociology, engineering, digital humanities). Data have become one of the most critical resources in today’s world.