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Machine Learning A-Z: Hands-On Python and Java
Machine Learning A-Z: Hands-On Java is a comprehensive online course tailored for participants who prefer to learn machine learning concepts and techniques using the Java programming language. The course provides a hands-on introduction to machine learning algorithms and applications, with a focus on Java-based tools and libraries.
- Introduction to Machine Learning with Java: Participants will be introduced to the fundamentals of machine learning and the Java programming language, setting the stage for building machine learning models using Java.
- Data Handling and Processing: The course covers techniques for data handling, manipulation, and preprocessing in Java, including data loading, cleansing, transformation, and feature engineering.
- Supervised and Unsupervised Learning Algorithms: Participants will explore a range of supervised and unsupervised learning algorithms implemented in Java, such as decision trees, k-nearest neighbors (KNN), naive Bayes, support vector machines (SVM), and clustering algorithms.
- Model Evaluation and Validation: The course teaches participants how to evaluate and validate machine learning models using Java-based metrics and techniques, including cross-validation, confusion matrices, and performance evaluation.
- Java Machine Learning Libraries: Participants will gain proficiency in Java-based machine learning libraries and frameworks, such as Weka, MOA (Massive Online Analysis), and Deeplearning4j.
- Hands-On Projects and Case Studies: The course includes hands-on projects and case studies that allow participants to apply machine learning algorithms and techniques to real-world datasets and solve practical problems using Java.
Certification
Upon successful completion of the course requirements, participants may receive a certificate of completion, indicating their proficiency in Machine Learning A-Z: Hands-On Java.