From Math to Mobile AI: Building and Deploying Machine Learning with C++
Sub Category
- Other IT & Software
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Objectives
- Understand the foundations of machine learning and apply mathematical concepts like linear algebra to real-world ML problems.
- Deploy machine learning models into production, including serialization, ONNX export, experiment tracking, and mobile deployment with real-time applications.
- Implement machine learning algorithms in C++, including regression, classification, clustering, anomaly detection, and recommender systems.
- Build and optimize deep learning models such as neural networks, convolutional networks, and transformers, while leveraging transfer learning techniques.
Pre Requisites
- Basic knowledge of C++ programming (variables, functions, and object-oriented programming).
- Some exposure to mathematics (linear algebra, probability, and statistics are helpful but not mandatory).
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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