About this Course
최근 조회 32,431

다음의 1/1개 강좌

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

완료하는 데 약 16시간 필요

권장: 5 Weeks, 3 - 5 hours per week...

영어

자막: 영어, 중국어 (간체자)

귀하가 습득할 기술

Machine Learning ConceptsKnimeMachine LearningApache Spark

다음의 1/1개 강좌

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

완료하는 데 약 16시간 필요

권장: 5 Weeks, 3 - 5 hours per week...

영어

자막: 영어, 중국어 (간체자)

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 24분 필요

Welcome

...
2 videos (Total 14 min)
2개의 동영상
Summary of Big Data Integration and Processing10m
완료하는 데 3시간 필요

Introduction to Machine Learning with Big Data

...
7 videos (Total 45 min), 7 readings, 1 quiz
7개의 동영상
Categories Of Machine Learning Techniques7m
Machine Learning Process3m
Goals and Activities in the Machine Learning Process10m
CRISP-DM5m
Scaling Up Machine Learning Algorithms5m
Tools Used in this Course5m
7개의 읽기 자료
Slides: Machine Learning Overview and Applications25m
Downloading, Installing and Using KNIME1h
Downloading and Installing the Cloudera VM Instructions (Windows)10m
Downloading and Installing the Cloudera VM Instructions (Mac)10m
Instructions for Downloading Hands On Datasets10m
Instructions for Starting Jupyter10m
PDFs of Readings for Week 1 Hands-On10m
1개 연습문제
Machine Learning Overview20m
2
완료하는 데 3시간 필요

Data Exploration

...
6 videos (Total 39 min), 5 readings, 2 quizzes
6개의 동영상
Data Exploration4m
Data Exploration through Summary Statistics7m
Data Exploration through Plots8m
Exploring Data with KNIME Plots9m
Data Exploration in Spark5m
5개의 읽기 자료
Slides: Data Exploration Overview and Terminology10m
Description of Daily Weather Dataset10m
Exploring Data with KNIME Plots40m
Data Exploration in Spark10m
PDFs of Activities for Data Exploration Hands-On Readings10m
2개 연습문제
Data Exploration20m
Data Exploration in KNIME and Spark Quiz20m
완료하는 데 3시간 필요

Data Preparation

...
8 videos (Total 42 min), 4 readings, 2 quizzes
8개의 동영상
Data Quality4m
Addressing Data Quality Issues4m
Feature Selection5m
Feature Transformation5m
Dimensionality Reduction7m
Handling Missing Values in KNIME5m
Handling Missing Values in Spark5m
4개의 읽기 자료
Slides: Data Preparation for Machine Learning30m
Handling Missing Values in KNIME20m
Handling Missing Values in Spark10m
PDFs for Data Preparation Hands-On Readings10m
2개 연습문제
Data Preparation25m
Handling Missing Values in KNIME and Spark Quiz20m
3
완료하는 데 4시간 필요

Classification

...
8 videos (Total 60 min), 7 readings, 2 quizzes
8개의 동영상
Building and Applying a Classification Model5m
Classification Algorithms2m
k-Nearest Neighbors4m
Decision Trees13m
Naïve Bayes14m
Classification using Decision Tree in KNIME8m
Classification in Spark6m
7개의 읽기 자료
Slides: What is Classification?10m
Slides: Classification Algorithms10m
Classification using Decision Tree in KNIME45m
Interpreting a Decision Tree in KNIME20m
Instructions for Changing the Number of Cloudera VM CPUs10m
Classification in Spark45m
PDFs for Classification Hands-On Readings10m
2개 연습문제
Classification20m
Classification in KNIME and Spark Quiz16m
4
완료하는 데 3시간 필요

Evaluation of Machine Learning Models

...
7 videos (Total 42 min), 7 readings, 2 quizzes
7개의 동영상
Overfitting in Decision Trees3m
Using a Validation Set9m
Metrics to Evaluate Model Performance10m
Confusion Matrix7m
Evaluation of Decision Tree in KNIME3m
Evaluation of Decision Tree in Spark2m
7개의 읽기 자료
Slides: Overfitting: What is it and how would you prevent it?10m
Slides: Model evaluation metrics and methods10m
Evaluation of Decision Tree in KNIME30m
Completed KNIME Workflows10m
Evaluation of Decision Tree in Spark20m
Comparing Classification Results for KNIME and Spark10m
PDFs for Evaluation of Machine Learning Models Hands-On Readings10m
2개 연습문제
Model Evaluation20m
Model Evaluation in KNIME and Spark Quiz16m
4.6
223개의 리뷰Chevron Right

48%

이 강좌를 수료한 후 새로운 경력 시작하기

43%

이 강좌를 통해 확실한 경력상 이점 얻기

15%

급여 인상 또는 승진하기

Machine Learning With Big Data의 최상위 리뷰

대학: PTJan 9th 2017

The course was the best introduction I had for machine learning. Helped me a lot to understand different concepts from people who already know about the subject and I didn't have any idea.

대학: PRJul 19th 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.

강사

Avatar

Mai Nguyen

Lead for Data Analytics
San Diego Supercomputer Center
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Ilkay Altintas

Chief Data Science Officer
San Diego Supercomputer Center

캘리포니아 샌디에고 대학교 정보

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....

빅 데이터 전문 분야 정보

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....
빅 데이터

자주 묻는 질문

  • 강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.

  • 강좌를 등록하면 전문 분야의 모든 강좌에 접근할 수 있고 강좌를 완료하면 수료증을 취득할 수 있습니다. 전자 수료증이 성취도 페이지에 추가되며 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 내용만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.

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