MACHINE LEARNING: (6 Months)
Description
What will you learn
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• Understanding popular ML algorithms with their associated mathematical foundations for appreciating these algorithms.
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• Capability to implement basic algorithms using basic machine learning libraries mostly in python. Gain hands-on experience in applying ML to problems encountered in various domains. In addition, obtain exposure to high-level ML libraries or frameworks such as TensorFlow, PyTorch.
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• Make aware of the role of data in the future of computing, and also in solving real-world problems using machine learning algorithms.
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• Help connect real-world problems to appropriate ML algorithm(s) for solving them. Enable formulating real world problems as machine learning tasks.
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• Appreciate the mathematical background behind popular ML algorithms.
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• Ensure awareness about importance of core CS principles such as algorithmic thinking and systems design in ML
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• Have sound mathematical understanding of popular ML algorithms
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• Preparedness to use state of the art machine learning algorithms in formulating and solving new problems.
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• Capability to train (or solve optimization problems) ML models with applications in real-world use cases.
Requirements
- Graduation (relevant) / Master’s degree (non-relevant)
Lessons
- 1 Lessons
- 00:00:00 Hours
- • Motivation and role of machine learning in computer science and problem solving • Representation(features), linear transformations, • Linear transformations and matrix vector operations in the context of data and representation. • Problem formulations
About instructor
