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· 분류 : 외국도서 > 컴퓨터 > 데이터베이스 관리 > 일반
· ISBN : 9781484256688
· 쪽수 : 355쪽
· 출판일 : 2020-02-23
목차
Chapter 1: Introduction to Apache Spark
Introduction to Spark
Architecture
Spark SQL, Dataset and DataFrames API
Spark Data Sources
Spark Streaming
Graph Processing
Spark MLlib
Chapter 2: Introduction to Machine Learning and Spark MLlib
Introduction to Machine Learning
Supervised
Regression
Classification
Unsupervised
ClusteringAnomaly Detection
Principal Component Analysis
Recommendations
Collaborative Filtering
Content Based Filtering
Association Rules
Deep Learning
Reinforcement Learning
High Performance Machine Learning with Spark MLlib
Spark ML Pipelines
DataFrame
Pipeline components
Transformers
Estimators
Spark ML Example
Chapter 3: Supervised Learning
Classification
Logistic Regression
Random Forest
Naive Bayes
Support Vector Machine
XGBoost
LightGBM
Regression
Simple Linear Regression with Linear RegressionMultiple Linear Regression with XGBoost
Chapter 4: Unsupervised Learning
KmeansII Clustering
Latent Dirichlet Allocation - Topic Modelling
Introduction to Natural Language Processing
SparkNLP from John Snow Labs
Stanford CoreNLP for Spark
Isolation Forest - Anomaly Detection
Principal Component Analysis
Chapter 5: Recommendations
Collaborative Filtering with ALS
Content-based Filtering with TF-IDF and DIMSUM
Recommending with Association Rules using Frequency Pattern Mining
Chapter 6: Graph Analysis
Introduction to Graph Processing
Introduction to GraphX and GraphFrames
Graph Operators
Graph Algorithms
PageRank
Connected Components
Triangle Counting
Chapter 7: Deep Learning
Introduction to Deep Learning
Deep Learning with SparkDistributed Deep Learning with Keras and Spark
