關於此課程：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
此課程適用人群：This course is for those new to data science. Completion of “Big Data Integration and Processing” is recommended. No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments. Refer to the specialization technical requirements for complete hardware and software specifications.
製作方： University of California San Diego
教學方： Mai Nguyen, Lead for Data Analytics
San Diego Supercomputer Center教學方： Ilkay Altintas, Chief Data Science Officer
San Diego Supercomputer Center
| 基本信息 | 課程 4（共 6 門，Big Data Specialization ） |
| 承諾學習時間 | 5 Weeks, 3 - 5 hours per week |
| 語言 | English |
| 如何通過 | 通過所有計分作業以完成課程。 |
| 用戶評分 |
授課大綱
第 1 週
Welcome
2 個視頻
- 視頻: Summary of Big Data Integration and Processing
- Discussion Prompt: Getting to Know You: Tell us about yourself and why you are taking this course.
- Discussion Prompt: Discussion Forum for Course Content Issues
Introduction to Machine Learning with Big Data
7 個視頻, 7 個閱讀材料
- 視頻: Categories Of Machine Learning Techniques
- Reading: Slides: Machine Learning Overview and Applications
- Discussion Prompt: Machine Learning in Everyday Life
- 視頻: Machine Learning Process
- 視頻: Goals and Activities in the Machine Learning Process
- 視頻: CRISP-DM
- 視頻: Scaling Up Machine Learning Algorithms
- 視頻: Tools Used in this Course
- Reading: Downloading, Installing and Using KNIME
- Reading: Downloading and Installing the Cloudera VM Instructions (Windows)
- Reading: Downloading and Installing the Cloudera VM Instructions (Mac)
- Reading: Instructions for Downloading Hands On Datasets
- Reading: Instructions for Starting Jupyter
- Reading: PDFs of Readings for Week 1 Hands-On
已評分: Machine Learning Overview
第 2 週
Data Exploration
6 個視頻, 5 個閱讀材料
- 視頻: Data Exploration
- 視頻: Data Exploration through Summary Statistics
- 視頻: Data Exploration through Plots
- Discussion Prompt: What's Wrong with Pie Charts?
- Reading: Slides: Data Exploration Overview and Terminology
- Reading: Description of Daily Weather Dataset
- Reading: Exploring Data with KNIME Plots
- 視頻: Exploring Data with KNIME Plots
- Reading: Data Exploration in Spark
- 視頻: Data Exploration in Spark
- Reading: PDFs of Activities for Data Exploration Hands-On Readings
已評分: Data Exploration
已評分: Data Exploration in KNIME and Spark Quiz
Data Preparation
8 個視頻, 4 個閱讀材料
- 視頻: Data Quality
- Discussion Prompt: Quality Issues with Real Data
- 視頻: Addressing Data Quality Issues
- 視頻: Feature Selection
- 視頻: Feature Transformation
- 視頻: Dimensionality Reduction
- Discussion Prompt: Domain Knowledge in Data Preparation
- Reading: Slides: Data Preparation for Machine Learning
- Reading: Handling Missing Values in KNIME
- 視頻: Handling Missing Values in KNIME
- Reading: Handling Missing Values in Spark
- 視頻: Handling Missing Values in Spark
- Reading: PDFs for Data Preparation Hands-On Readings
已評分: Data Preparation
已評分: Handling Missing Values in KNIME and Spark Quiz
第 3 週
Classification
8 個視頻, 7 個閱讀材料
- 視頻: Building and Applying a Classification Model
- Reading: Slides: What is Classification?
- 視頻: Classification Algorithms
- 視頻: k-Nearest Neighbors
- 視頻: Decision Trees
- 視頻: Naïve Bayes
- Reading: Slides: Classification Algorithms
- Reading: Classification using Decision Tree in KNIME
- 視頻: Classification using Decision Tree in KNIME
- Reading: Interpreting a Decision Tree in KNIME
- Reading: Instructions for Changing the Number of Cloudera VM CPUs
- Reading: Classification in Spark
- 視頻: Classification in Spark
- Discussion Prompt: Why Exclude Relative Humidity?
- Reading: PDFs for Classification Hands-On Readings
已評分: Classification
已評分: Classification in KNIME and Spark Quiz
第 4 週
Evaluation of Machine Learning Models
7 個視頻, 7 個閱讀材料
- 視頻: Overfitting in Decision Trees
- 視頻: Using a Validation Set
- Reading: Slides: Overfitting: What is it and how would you prevent it?
- 視頻: Metrics to Evaluate Model Performance
- 視頻: Confusion Matrix
- Discussion Prompt: Model Interpretability vs. Accuracy
- Reading: Slides: Model evaluation metrics and methods
- Reading: Evaluation of Decision Tree in KNIME
- 視頻: Evaluation of Decision Tree in KNIME
- Reading: Completed KNIME Workflows
- Reading: Evaluation of Decision Tree in Spark
- 視頻: Evaluation of Decision Tree in Spark
- Reading: Comparing Classification Results for KNIME and Spark
- Reading: PDFs for Evaluation of Machine Learning Models Hands-On Readings
已評分: Model Evaluation
已評分: Model Evaluation in KNIME and Spark Quiz
第 5 週
Regression, Cluster Analysis, and Association Analysis
8 個視頻, 6 個閱讀材料
- 視頻: Linear Regression
- Reading: Slides: Regression
- 視頻: Cluster Analysis
- 視頻: k-Means Clustering
- Reading: Slides: Cluster Analysis
- Discussion Prompt: Clustering Applications
- 視頻: Association Analysis
- 視頻: Association Analysis in Detail
- Reading: Slides: Association Analysis
- Discussion Prompt: Applications of Association Analysis
- 視頻: Machine Learning With Big Data - Final Remarks
- Reading: Description of Minute Weather Dataset
- Reading: Cluster Analysis in Spark
- 視頻: Cluster Analysis in Spark
- Reading: PDFs of Cluster Analysis in Spark Hands-On Readings
已評分: Regression, Cluster Analysis, & Association Analysis
已評分: Cluster Analysis in Spark Quiz
常見問題解答
運作方式
Coursework
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製作方
University of California San Diego
UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.
價格
| 購買課程 | |
|---|---|
| 訪問課程材料 | 可用 |
| 訪問評分的材料 | 可用 |
| 收到最終成績 | 可用 |
| 獲得可共享的課程證書 | 可用 |
評分和審閱
very good topic learnt from you
It was very interesting course. I enjoyed learning.
Amazing training on ML for people starting their first experiences with the topic. Practical and easy to understand examples that can be further extended by the student.
My name is Jose Antonio. I am looking for a new Data Scientist career (https://www.linkedin.com/in/joseantonio11)
I did this specialization to get new knowledge about Machine Learning and better understand the technology and your practical applications.
The course was excellent and the classes well taught by teachers.
Congratulations to Coursera team and Instructors.
Regards.
Jose Antonio.