EBOOK
Ultimate Java for Data Analytics and Machine Learning
Unlock Java's Ecosystem for Data Analysis and Machine Learning Using WEKA, JavaML, JFreeChart, and D
Abhishek Kumar(0)
About
Empower Your Data Insights with Java's Top Tools and Frameworks.
Book Description
This book is a comprehensive guide to data analysis using Java. It starts with the fundamentals, covering the purpose of data analysis, different data types and structures, and how to pre-process datasets. It then introduces popular Java libraries like WEKA and Rapidminer for efficient data analysis.
The middle section of the book dives deeper into statistical techniques like descriptive analysis and random sampling, along with practical skills in working with relational databases (JDBC, SQL, MySQL) and NoSQL databases. It also explores various analysis methods like regression, classification, and clustering, along with applications in business intelligence and time series prediction.
The final part of the book gives a brief overview of big data analysis with Java frameworks like MapReduce, and introduces deep learning with the Deeplearning4J library. Whether you're new to data analysis or want to improve your Java skills, this book offers a step-by-step approach with real-world examples to help you master data analysis using Java.
Table of Contents
1. Data Analytics Using Java
2. Datasets
3. Data Visualization
4. Java Machine Learning Libraries
5. Statistical Analysis
6. Relational Databases
7. Regression Analysis
8. Classification?
Analysis
9. Sentiment Analysis
10. Cluster Analysis
11. Working with NoSQL Databases
12. Recommender Systems
13. Applications of Data Analysis
14. Big Data Analysis with Java
15. Deep Learning with Java
Index
Book Description
This book is a comprehensive guide to data analysis using Java. It starts with the fundamentals, covering the purpose of data analysis, different data types and structures, and how to pre-process datasets. It then introduces popular Java libraries like WEKA and Rapidminer for efficient data analysis.
The middle section of the book dives deeper into statistical techniques like descriptive analysis and random sampling, along with practical skills in working with relational databases (JDBC, SQL, MySQL) and NoSQL databases. It also explores various analysis methods like regression, classification, and clustering, along with applications in business intelligence and time series prediction.
The final part of the book gives a brief overview of big data analysis with Java frameworks like MapReduce, and introduces deep learning with the Deeplearning4J library. Whether you're new to data analysis or want to improve your Java skills, this book offers a step-by-step approach with real-world examples to help you master data analysis using Java.
Table of Contents
1. Data Analytics Using Java
2. Datasets
3. Data Visualization
4. Java Machine Learning Libraries
5. Statistical Analysis
6. Relational Databases
7. Regression Analysis
8. Classification?
Analysis
9. Sentiment Analysis
10. Cluster Analysis
11. Working with NoSQL Databases
12. Recommender Systems
13. Applications of Data Analysis
14. Big Data Analysis with Java
15. Deep Learning with Java
Index