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Machine Learning Techniques

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The program builds upon the fundamental concepts of "Machine Learning Foundations," with an emphasis on practical and advanced models. It investigates the integration of a variety of features, the distillation of concealed features, and the combination of predictive features to improve the capabilities of machine learning.

Key AI Functions:aritificial intelligence,machince learning,deep learning,ai & machine learning

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Description for Machine Learning Techniques

Embedding a Large Number of Features: Acquire the skills necessary to represent data with multiple embedded features in order to improve predictive modeling.
Merging Predictive Features: Comprehend the process of combining a variety of predictive features to enhance the accuracy and efficacy of the model.
Uncovering and Utilizing latent Features: Acquire a deeper understanding of the process of identifying and leveraging latent features in datasets to enhance performance.
Constructing Realistic Models: Create machine learning models that are practical and that utilize sophisticated feature representation and manipulation techniques.

Level: Intermediate

Certification Degree: Yes

Languages the Course is Available: 21

Offered by: On Coursera provided by National Taiwan University

Duration: 3 weeks at 6 hours a week

Schedule: Flexible

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