目錄(70章)
倒序
- coverpage
- Scala Data Analysis Cookbook
- Credits
- About the Author
- About the Reviewers
- www.PacktPub.com
- Support files eBooks discount offers and more
- Preface
- Apache Flink
- Scalding
- Saddle
- Spire
- Akka
- Accord
- What this book covers
- What you need for this book
- Who this book is for
- Sections
- Conventions
- Reader feedback
- Customer support
- Chapter 1. Getting Started with Breeze
- Introduction
- Getting Breeze – the linear algebra library
- Working with vectors
- Working with matrices
- Vectors and matrices with randomly distributed values
- Reading and writing CSV files
- Chapter 2. Getting Started with Apache Spark DataFrames
- Introduction
- Getting Apache Spark
- Creating a DataFrame from CSV
- Manipulating DataFrames
- Creating a DataFrame from Scala case classes
- Chapter 3. Loading and Preparing Data – DataFrame
- Introduction
- Loading more than 22 features into classes
- Loading JSON into DataFrames
- Storing data as Parquet files
- Using the Avro data model in Parquet
- Loading from RDBMS
- Preparing data in Dataframes
- Chapter 4. Data Visualization
- Introduction
- Visualizing using Zeppelin
- Creating scatter plots with Bokeh-Scala
- Creating a time series MultiPlot with Bokeh-Scala
- Chapter 5. Learning from Data
- Introduction
- Supervised and unsupervised learning
- Gradient descent
- Predicting continuous values using linear regression
- Binary classification using LogisticRegression and SVM
- Binary classification using LogisticRegression with Pipeline API
- Clustering using K-means
- Feature reduction using principal component analysis
- Chapter 6. Scaling Up
- Introduction
- Building the Uber JAR
- Submitting jobs to the Spark cluster (local)
- Running the Spark Standalone cluster on EC2
- Running the Spark Job on Mesos (local)
- Running the Spark Job on YARN (local)
- Chapter 7. Going Further
- Introduction
- Using Spark Streaming to subscribe to a Twitter stream
- Using Spark as an ETL tool
- Using StreamingLogisticRegression to classify a Twitter stream using Kafka as a training stream
- Using GraphX to analyze Twitter data
- Index 更新時間：2021-07-09 21:24:31
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