Machine Learning With Big Data

Course Content

Module 1: Welcome

Welcome to Machine Learning With Big Data

00:00
Summary of Big Data Integration and Processing

00:00

2 discussion prompts

Module 2: Introduction to Machine Learning with Big Data

7 readings

1 quiz

1 discussion prompt

Module 3: Data Exploration

5 readings

2 quizzes

1 discussion prompt

Module 4: Data Preparation

4 readings

2 quizzes

2 discussion prompts

Module 5: Classification

7 readings

2 quizzes

1 discussion prompt

Module 6: Evaluation of Machine Learning Models

7 readings

2 quizzes

1 discussion prompt

Module 7: Regression, Cluster Analytics and Association Analytics

6 readings

2 quizzes

2 discussion prompts

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What Will You Learn?

Course Content

Module 1: Welcome

Welcome to Machine Learning With Big Data

Summary of Big Data Integration and Processing

2 discussion prompts

Getting to Know You: Tell us about yourself and why you are taking this course

Discussion Forum for Course Content Issues

Module 2: Introduction to Machine Learning with Big Data

Machine Learning Overview

Categories Of Machine Learning Techniques

Machine Learning Process

Goals and Activities in the Machine Learning Process

CRISP-DM

Scaling Up Machine Learning Algorithms

Tools Used in this Course

7 readings

Slides: Machine Learning Overview and Applications

Downloading, Installing and Using KNIME

Downloading and Installing the Cloudera VM Instructions (Windows)

Downloading and Installing the Cloudera VM Instructions (Mac)

Instructions for Downloading Hands On Datasets

Instructions for Starting Jupyter

PDFs of Readings for Week 1 Hands-On

1 quiz

Machine Learning Overview

1 discussion prompt

Machine Learning in Everyday Life

Module 3: Data Exploration

Data Terminology

Data Exploration

Data Exploration through Summary Statistics

Data Exploration through Plots

Exploring Data with KNIME Plots

Data Exploration in Spark

5 readings

Slides: Data Exploration Overview and Terminology

Description of Daily Weather Dataset

Exploring Data with KNIME Plots

Data Exploration in Spark

PDFs of Activities for Data Exploration Hands-On Readings

2 quizzes

Data Exploration

Data Exploration in KNIME and Spark Quiz

1 discussion prompt

What’s Wrong with Pie Charts?

Module 4: Data Preparation

Data Preparation

Data Quality

Addressing Data Quality Issues

Feature Selection

Feature Transformation

Dimensionality Reduction

Handling Missing Values in KNIME

Handling Missing Values in Spark

4 readings

Slides: Data Preparation for Machine Learning

Handling Missing Values in KNIME

Handling Missing Values in Spark

PDFs for Data Preparation Hands-On Readings

2 quizzes

Data Preparation

Handling Missing Values in KNIME and Spark Quiz

2 discussion prompts

Quality Issues with Real Data

Domain Knowledge in Data Preparation

Module 5: Classification

Classification

Building and Applying a Classification Model

Classification Algorithms

k-Nearest Neighbors

Decision Trees

Naïve Bayes

Classification using Decision Tree in KNIME

Classification in Spark

7 readings

Slides: What is Classification?

Slides: Classification Algorithms

Classification using Decision Tree in KNIME

Interpreting a Decision Tree in KNIME