Course Highlights
  • Explore several classic Supervised and Unsupervised Learning algorithms and introductory Deep Learning topics.
  • Build and evaluate Machine Learning models utilizing popular Python libraries and compare each algorithm’s strengths and weaknesses.
  • Explain which Machine Learning models would be best to apply to a Machine Learning task based on the data’s properties.
  • Improve model performance by tuning hyperparameters and applying various techniques such as sampling and regularization.
  Write a Review

Machine Learning: Theory and Hands-on Practice with Python

Go to Free Course