ML Theory & Quizzes: Test your foundational knowledge in Algorithms, Math, Evaluation Metrics, and Core Concepts.
Sub Category
- IT Certifications
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Objectives
- Accurately define and differentiate between key Machine Learning terms and concepts commonly used in the industry.
- Differentiate effectively between supervised, unsupervised, and reinforcement learning paradigms and their appropriate use cases.
- Explain the fundamental mechanism and underlying assumptions of core models like Linear Regression and Logistic Regression.
- Interpret and apply common model evaluation metrics, including Precision, Recall, F1-Score, and accuracy.
- Describe the Bias-Variance Tradeoff in detail and outline robust strategies to mitigate model overfitting and underfitting.
- Calculate and correctly interpret the output generated by a Confusion Matrix for various classification problems.
- Understand the role of Gradient Descent and its variants (Stochastic, Mini-Batch) in optimizing machine learning models.
- Identify and apply appropriate regularization techniques (L1/L2) to enhance model generalization and prevent complexity.
- Master the core theoretical principles behind clustering algorithms such as K-Means and Hierarchical Clustering.
- Confidently answer complex theoretical and conceptual questions related to fundamental ML algorithms under pressure.
Pre Requisites
- Basic understanding of mathematical concepts (linear algebra and basic calculus) relevant to optimization.
- Familiarity with foundational Machine Learning concepts, models, and terminology.
- No specific coding knowledge (Python/R) is strictly required, as the focus is theoretical assessment.
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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