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.
提供：
このコースについて
77,314 最近の表示
受講生の就業成果
42%
コース終了後に新しいキャリアをスタートした
41%
コースが具体的なキャリアアップにつながった
14%
昇給や昇進につながった
習得するスキル
Machine Learning ConceptsKnimeMachine LearningApache Spark
受講生の就業成果
42%
コース終了後に新しいキャリアをスタートした
41%
コースが具体的なキャリアアップにつながった
14%
昇給や昇進につながった
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
次における6の4コース
柔軟性のある期限
スケジュールに従って期限をリセットします。
約18時間で修了
英語
字幕：英語, 韓国語, 中国語（簡体）
提供：
カリフォルニア大学サンディエゴ校
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.
シラバス - 本コースの学習内容
24分で修了
Welcome
24分で修了
2件のビデオ （合計14分）
2件のビデオ
Summary of Big Data Integration and Processing10 分
3時間で修了
Introduction to Machine Learning with Big Data
3時間で修了
7件のビデオ （合計45分）, 7 readings, 1 quiz
7件のビデオ
Categories Of Machine Learning Techniques7 分
Machine Learning Process3 分
Goals and Activities in the Machine Learning Process10 分
CRISP-DM5 分
Scaling Up Machine Learning Algorithms5 分
Tools Used in this Course5 分
7件の学習用教材
Slides: Machine Learning Overview and Applications25 分
Downloading, Installing and Using KNIME1 時間
Downloading and Installing the Cloudera VM Instructions (Windows)10 分
Downloading and Installing the Cloudera VM Instructions (Mac)10 分
Instructions for Downloading Hands On Datasets10 分
Instructions for Starting Jupyter10 分
PDFs of Readings for Week 1 Hands-On10 分
1の練習問題
Machine Learning Overview20 分
3時間で修了
Data Exploration
3時間で修了
6件のビデオ （合計39分）, 5 readings, 2 quizzes
6件のビデオ
Data Exploration4 分
Data Exploration through Summary Statistics7 分
Data Exploration through Plots8 分
Exploring Data with KNIME Plots9 分
Data Exploration in Spark5 分
5件の学習用教材
Slides: Data Exploration Overview and Terminology10 分
Description of Daily Weather Dataset10 分
Exploring Data with KNIME Plots40 分
Data Exploration in Spark10 分
PDFs of Activities for Data Exploration Hands-On Readings10 分
2の練習問題
Data Exploration20 分
Data Exploration in KNIME and Spark Quiz20 分
3時間で修了
Data Preparation
3時間で修了
8件のビデオ （合計42分）, 4 readings, 2 quizzes
8件のビデオ
Data Quality4 分
Addressing Data Quality Issues4 分
Feature Selection5 分
Feature Transformation5 分
Dimensionality Reduction7 分
Handling Missing Values in KNIME5 分
Handling Missing Values in Spark5 分
4件の学習用教材
Slides: Data Preparation for Machine Learning30 分
Handling Missing Values in KNIME20 分
Handling Missing Values in Spark10 分
PDFs for Data Preparation Hands-On Readings10 分
2の練習問題
Data Preparation25 分
Handling Missing Values in KNIME and Spark Quiz20 分
4時間で修了
Classification
4時間で修了
8件のビデオ （合計60分）, 7 readings, 2 quizzes
8件のビデオ
Building and Applying a Classification Model5 分
Classification Algorithms2 分
k-Nearest Neighbors4 分
Decision Trees13 分
Naïve Bayes14 分
Classification using Decision Tree in KNIME8 分
Classification in Spark6 分
7件の学習用教材
Slides: What is Classification?10 分
Slides: Classification Algorithms10 分
Classification using Decision Tree in KNIME45 分
Interpreting a Decision Tree in KNIME20 分
Instructions for Changing the Number of Cloudera VM CPUs10 分
Classification in Spark45 分
PDFs for Classification Hands-On Readings10 分
2の練習問題
Classification20 分
Classification in KNIME and Spark Quiz16 分
3時間で修了
Evaluation of Machine Learning Models
3時間で修了
7件のビデオ （合計42分）, 7 readings, 2 quizzes
7件のビデオ
Overfitting in Decision Trees3 分
Using a Validation Set9 分
Metrics to Evaluate Model Performance10 分
Confusion Matrix7 分
Evaluation of Decision Tree in KNIME3 分
Evaluation of Decision Tree in Spark2 分
7件の学習用教材
Slides: Overfitting: What is it and how would you prevent it?10 分
Slides: Model evaluation metrics and methods10 分
Evaluation of Decision Tree in KNIME30 分
Completed KNIME Workflows10 分
Evaluation of Decision Tree in Spark20 分
Comparing Classification Results for KNIME and Spark10 分
PDFs for Evaluation of Machine Learning Models Hands-On Readings10 分
2の練習問題
Model Evaluation20 分
Model Evaluation in KNIME and Spark Quiz16 分
レビュー
4.6
MACHINE LEARNING WITH BIG DATA からの人気レビュー
JCによりDec 8, 2018
Interesting material. Ran into several issues with the hands on that could have been avoided. Loved learning more about Neo4J. The section on Spark needed more time and additional descriptions.
MMによりJan 29, 2017
This is a valuable course in learning the basics of machine learning. but I was hoping to to get more hands on practice in this course. but overall, i learned a lot with the existing content.
JAによりMay 9, 2017
Great overview about the machine learning in general. There are still lots not covered specially the Neural Network algorithms. Learning Spark MLlib was great advantage of this course.
PRによりJul 18, 2018
Excellent course, I learned a lot about machine learning with big data, but most importantly I feel ready to take it into more complex level although I realized there is lots to learn.
BKによりMar 5, 2020
This is starting course for Machine Learning. Very well explained and after finishing this course, one will get interest in continuing and exploring further in Machine Learning field.
TAによりDec 26, 2019
The fact that the assignments are graded means that there’s incentive to work on them, solve problems, and ask questions. Traditional online courses don’t offer that incentive.
DDによりSep 6, 2017
Hands n exercises and corresponding quizzes are great !Content could be more detailed, but may be I felt it so given my past exposure to ML. I enjoyed learning Knime and Spark.
BCによりFeb 15, 2020
This has given me foundational knowledge in Machine Learning for someone who is not a practitioner. Thank you Mai Nguyen for the excellent course presentation. Keep it up.
SNによりDec 3, 2017
The precise definitions for many commonly used terms were very helpful. You do not find these details in many books or documents. Also, using KNIME was also interesting
NPによりJul 2, 2019
This course provides you starting point to start working in KNIME and helps you in explaining basic statistics concepts along with its application in KNIME and Spark
LOによりFeb 27, 2017
Very well explained course on Machine Learning. I am grateful for the highly insightful course like this. I will recommend this course for all data enthusiasts.
PUによりAug 24, 2018
This course strikes the right balance between theory and practice of introductory ML. The instructors have done a tremendous job of presenting the material.
ビッグデータ専門講座について
Drive better business decisions with an overview of how big data is organized, analyzed, and interpreted. Apply your insights to real-world problems and questions.
*********
Do you need to understand big data and how it will impact your business? This Specialization is for you. You will gain an understanding of what insights big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers. Previous programming experience is not required! You will be guided through the basics of using Hadoop with MapReduce, Spark, Pig and Hive. By following along with provided code, you will experience how one can perform predictive modeling and leverage graph analytics to model problems. This specialization will prepare you to ask the right questions about data, communicate effectively with data scientists, and do basic exploration of large, complex datasets. In the final Capstone Project, developed in partnership with data software company Splunk, you’ll apply the skills you learned to do basic analyses of big data.
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