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Course Description
Machine learning and neural networks are fast becoming pillars on which you can build intelligent applications. The course will begin by introducing you to Python and discussing using AI search algorithms. You will learn math-heavy topics, such as regression and classification, illustrated by Python examples.
You will then progress on to advanced AI techniques and concepts, and work on real-life data sets to form decision trees and clusters. You will be introduced to neural networks, which is a powerful tool benefiting from Moore’s law applied on 21st-century computing power. By the end of this course, you will feel confident and look forward to building your own AI applications with your newly-acquired skills!
The code bundle can be downloaded from here https://github.com/TrainingByPackt/Artificial-Intelligence-and-Machine-Learning-Fundamentals-eLearning
Target Audience
- Understand the importance, principles, and fields of AI
- Learn to implement basic artificial intelligence concepts with Python
- Apply regression and classification concepts to real-world problems
- Perform predictive analysis using decision trees and random forests
- Perform clustering using the k-means and mean shift algorithms
- Understand the fundamentals of deep learning via practical examples
Learning Objectives
- Understand the importance, principles, and fields of AI
- Learn to implement basic artificial intelligence concepts with Python
- Apply regression and classification concepts to real-world problems
- Perform predictive analysis using decision trees and random forests
- Perform clustering using the k-means and mean shift algorithms
- Understand the fundamentals of deep learning via practical examples
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