Java data science cookbook explore the power of MLlib, DL4j, Weka, and more
Recipes to help you overcome your data science hurdles using Java About This Book This book provides modern recipes in small steps to help an apprentice cook become a master chef in data science Use these recipes to obtain, clean, analyze, and learn from your data Learn how to get your data science...
| Otros Autores: | |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Birmingham, [England] ; Mumbai, [India] :
Packt
2017.
|
| Edición: | 1st edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630075506719 |
Tabla de Contenidos:
- Cover
- Credits
- About the Author
- About the Reviewer
- www.PacktPub.com
- Customer Feedback
- Table of Contents
- Preface
- Chapter 1: Obtaining and Cleaning Data
- Introduction
- Retrieving all filenames from hierarchical directories using Java
- Getting ready
- How to do it…
- Retrieving all filenames from hierarchical directories using Apache Commons IO
- Getting ready
- How to do it…
- Reading contents from text files all at once using Java 8
- How to do it…
- Reading contents from text files all at once using Apache Commons IO
- Getting ready
- How to do it…
- Extracting PDF text using Apache Tika
- Getting ready
- How to do it…
- Cleaning ASCII text files using Regular Expressions
- How to do it…
- Parsing Comma Separated Value (CSV) Files using Univocity
- Getting ready
- How to do it…
- Parsing Tab Separated Value (TSV) file using Univocity
- Getting ready
- How to do it…
- Parsing XML files using JDOM
- Getting ready
- How to do it…
- Writing JSON files using JSON.simple
- Getting ready
- How to do it…
- Reading JSON files using JSON.simple
- Getting ready
- How to do it …
- Extracting web data from a URL using JSoup
- Getting ready
- How to do it…
- Extracting web data from a website using Selenium Webdriver
- Getting ready
- How to do it…
- Reading table data from a MySQL database
- Getting ready
- How to do it…
- Chapter 2: Indexing and Searching Data
- Introduction
- Indexing data with Apache Lucene
- Getting ready
- How to do it…
- How it works…
- Searching indexed data with Apache Lucene
- Getting ready
- How to do it…
- Chapter 3: Analyzing Data Statistically
- Introduction
- Generating descriptive statistics
- How to do it…
- Generating summary statistics
- How to do it…
- Generating summary statistics from multiple distributions
- How to do it…
- There's more….
- Computing frequency distribution
- How to do it…
- Counting word frequency in a string
- How to do it…
- How it works…
- Counting word frequency in a string using Java 8
- How to do it…
- Computing simple regression
- How to do it…
- Computing ordinary least squares regression
- How to do it…
- Computing generalized least squares regression
- How to do it…
- Calculating covariance of two sets of data points
- How to do it…
- Calculating Pearson's correlation of two sets of data points
- How to do it…
- Conducting a paired t-test
- How to do it…
- Conducting a Chi-square test
- How to do it…
- Conducting the one-way ANOVA test
- How to do it…
- Conducting a Kolmogorov-Smirnov test
- How to do it…
- Chapter 4: Learning from Data - Part 1
- Introduction
- Creating and saving an Attribute-Relation File Format (ARFF) file
- How to do it…
- Cross-validating a machine learning model
- How to do it…
- Classifying unseen test data
- Getting ready
- How to do it…
- Classifying unseen test data with a filtered classifier
- How to do it…
- Generating linear regression models
- How to do it…
- Generating logistic regression models
- How to do it…
- Clustering data points using the KMeans algorithm
- How to do it…
- Clustering data from classes
- How to do it…
- Learning association rules from data
- Getting ready
- How to do it…
- Selecting features/attributes using the low-level method, the filtering method, and the meta-classifier method
- Getting ready
- How to do it…
- Chapter 5: Learning from Data - Part 2
- Introduction
- Applying machine learning on data using Java Machine Learning (Java-ML) library
- Getting ready
- How to do it…
- Classifying data points using the Stanford classifier
- Getting ready
- How to do it…
- How it works…
- Classifying data points using Massive Online Analysis (MOA).
- Getting ready
- How to do it…
- Classifying multilabeled data points using Mulan
- Getting ready
- How to do it…
- Chapter 6: Retrieving Information from Text Data
- Introduction
- Detecting tokens (words) using Java
- Getting ready
- How to do it…
- Detecting sentences using Java
- Getting ready
- How to do it…
- Detecting tokens (words) and sentences using OpenNLP
- Getting ready
- How to do it…
- Retrieving lemma, part-of-speech, and recognizing named entities from tokens using Stanford CoreNLP
- Getting ready
- How to do it…
- Measuring text similarity with Cosine Similarity measure using Java 8
- Getting ready
- How to do it…
- Extracting topics from text documents using Mallet
- Getting ready
- How to do it…
- Classifying text documents using Mallet
- Getting ready
- How to do it…
- Classifying text documents using Weka
- Getting ready
- How to do it…
- Chapter 7: Handling Big Data
- Introduction
- Training an online logistic regression model using Apache Mahout
- Getting ready
- How to do it…
- Applying an online logistic regression model using Apache Mahout
- Getting ready
- How to do it…
- Solving simple text mining problems with Apache Spark
- Getting ready
- How to do it…
- Clustering using KMeans algorithm with MLib
- Getting ready
- How to do it…
- Creating a linear regression model with MLib
- Getting ready
- How to do it…
- Classifying data points with Random Forest model using MLib
- Getting ready
- How to do it…
- Chapter 8: Learn Deeply from Data
- Introduction
- Creating a Word2vec neural net using Deep Learning for Java (DL4j)
- How to do it…
- How it works…
- There's more
- Creating a Deep Belief neural net using Deep Learning for Java (DL4j)
- How to do it…
- How it works…
- Creating a deep autoencoder using Deep Learning for Java (DL4j)
- How to do it….
- How it works…
- Chapter 9: Visualizing Data
- Introduction
- Plotting a 2D sine graph
- Getting ready
- How to do it…
- Plotting histograms
- Getting ready
- How to do it…
- Plotting a bar chart
- Getting ready
- How to do it…
- Plotting box plots or whisker diagrams
- Getting ready
- How to do it…
- Plotting scatter plots
- Getting ready
- How to do it…
- Plotting donut plots
- Getting ready
- How to do it…
- Plotting area graphs
- Getting ready
- How to do it…
- Index.
