This is the code repository for Machine Learning Projects with Java [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
Developers are worried about using various algorithms to solve different problems. This course is a perfect guide to identifying the best solution to efficiently build machine learning projects for different use cases to solve real-world problems.
In this course, you will learn how to build a model that takes complex feature vector form sensor data and classifies data points into classes with similar characteristics. Then you will predict the price of a house based on historical data. Finally, you will build a Deep Learning model that can guess personality traits using labeled data.
By the end of this course, you will have mastered each machine learning domain and will be able to build your own powerful projects at work
- Perform classification using the Weka Library.
- Implement Pattern Recognition of non-labeled data
- Build Regression models for data with multiple features
- Save trained models for further reusability
- Learn how to perform cross-validation
- Leverage Deep Learning in ML problems
- Implement Natural Language Processing with Deep Learning
To fully benefit from the coverage included in this course, you will need:
This course is for Java developers who now want to extend their skillset in Machine Learning and would like to achieve this with ease using Java.
This course will also appeal to someone who has a basic understanding of ML concepts but now wants to learn how to implement it with Java.
This course has the following software requirements:
This course has the following software requirements:
• IntelliJ IDEA
• Java JDK 8 or later
• Scala SDK
This course has been tested on the following system configuration:
• OS: MacOSX
• Processor: I7 2.8
• Memory: 16GB
• Hard Disk Space: 200MB
• Video Card: 256MB Video Memory