Enroll Here: Machine Learning FREE Certification – MathWorks
The course typically covers the following topics:
- Introduction to Machine Learning: An overview of what machine learning is and its applications.
- Data Preprocessing: Techniques for preparing data for machine learning tasks, such as cleaning, normalization, and feature selection.
- Supervised Learning: Learning from labeled data, including algorithms like decision trees, k-nearest neighbors, and support vector machines.
- Unsupervised Learning: Learning from unlabeled data, including clustering and dimensionality reduction methods.
- Model Evaluation: Techniques for assessing the performance of machine learning models and avoiding overfitting.
- Deep Learning: An introduction to neural networks and deep learning techniques.
- Throughout the course, participants work with real-world datasets and use MATLAB to implement and experiment with various machine learning algorithms and techniques.
