Data Science

ML Theory & Hands-on: Python Specialization

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Learn to develop, assess, and enhance machine learning models using Python libraries, covering introductory deep learning, supervised, and unsupervised learning algorithms.

Key AI Functions:Unsupervised Learning, Python Programming, Deep Learning, hyperparameter tuning, Supervised Learning

Description for ML Theory & Hands-on: Python Specialization

  • Examine a variety of introductory Deep Learning topics and classic Supervised and Unsupervised Learning algorithms.
  • Develop and assess machine learning models by employing widely used Python libraries and contrasting the advantages and disadvantages of each algorithm.
  • Specify the most appropriate Machine Learning models to apply to a Machine Learning task in accordance with the properties of the data.
  • Enhance model efficacy by implementing a variety of techniques, including regularization and sampling, and tuning hyperparameters.
  • Level: Intermediate

    Certification Degree: Yes

    Languages the Course is Available: 21

    Offered by: On Coursera provided by University of Colorado Boulder

    Duration: 3 months at 10 hours a week

    Schedule: Flexible

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