Machine Learning With Big Data
- Offered byCoursera
- Public/Government Institute
Machine Learning With Big Data at Coursera Overview
Duration | 22 hours |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Machine Learning With Big Data at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 4 of 6 in the Big Data Specialization
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Approx. 22 hours to complete
- English Subtitles: Arabic, French, Portuguese (European), Chinese (Simplified), Italian, Vietnamese, Korean, German, Russian, English, Spanish
Machine Learning With Big Data at Coursera Course details
- Want to make sense of the volumes of data you have collected? Need to incorporate data-driven decisions into your process? This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up to big data problems.
- At the end of the course, you will be able to:
- ? Design an approach to leverage data using the steps in the machine learning process.
- ? Apply machine learning techniques to explore and prepare data for modeling.
- ? Identify the type of machine learning problem in order to apply the appropriate set of techniques.
- ? Construct models that learn from data using widely available open source tools.
- ? Analyze big data problems using scalable machine learning algorithms on Spark.
- Software Requirements:
- Cloudera VM, KNIME, Spark
Machine Learning With Big Data at Coursera Curriculum
Welcome
Welcome to Machine Learning With Big Data
Summary of Big Data Integration and Processing
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
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
Machine Learning Overview
Data Exploration
Data Terminology
Data Exploration
Data Exploration through Summary Statistics
Data Exploration through Plots
Exploring Data with KNIME Plots
Data Exploration in Spark
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
Data Exploration
Data Exploration in KNIME and Spark Quiz
Data Preparation
Data Quality
Addressing Data Quality Issues
Feature Selection
Feature Transformation
Dimensionality Reduction
Handling Missing Values in KNIME
Handling Missing Values in Spark
Slides: Data Preparation for Machine Learning
Handling Missing Values in KNIME
Handling Missing Values in Spark
PDFs for Data Preparation Hands-On Readings
Data Preparation
Handling Missing Values in KNIME and Spark Quiz
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
Slides: What is Classification?
Slides: Classification Algorithms
Classification using Decision Tree in KNIME
Interpreting a Decision Tree in KNIME
Instructions for Changing the Number of Cloudera VM CPUs
Classification in Spark
PDFs for Classification Hands-On Readings
Classification
Classification in KNIME and Spark Quiz
Evaluation of Machine Learning Models
Generalization and Overfitting
Overfitting in Decision Trees
Using a Validation Set
Metrics to Evaluate Model Performance
Confusion Matrix
Evaluation of Decision Tree in KNIME
Evaluation of Decision Tree in Spark
Slides: Overfitting: What is it and how would you prevent it?
Slides: Model evaluation metrics and methods
Evaluation of Decision Tree in KNIME
Completed KNIME Workflows
Evaluation of Decision Tree in Spark
Comparing Classification Results for KNIME and Spark
PDFs for Evaluation of Machine Learning Models Hands-On Readings
Model Evaluation
Model Evaluation in KNIME and Spark Quiz
Regression, Cluster Analysis, and Association Analysis
Regression Overview
Linear Regression
Cluster Analysis
k-Means Clustering
Association Analysis
Association Analysis in Detail
Machine Learning With Big Data - Final Remarks
Cluster Analysis in Spark
Slides: Regression
Slides: Cluster Analysis
Slides: Association Analysis
Description of Minute Weather Dataset
Cluster Analysis in Spark
PDFs of Cluster Analysis in Spark Hands-On Readings
Regression, Cluster Analysis, & Association Analysis
Cluster Analysis in Spark Quiz
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