In this course, you will :
- Examine a number of classic Supervised and Unsupervised Learning algorithms, as well as some introductory Deep Learning topics.
- Create and evaluate Machine Learning models using popular Python libraries, and compare the strengths and weaknesses of each algorithm.
- Explain which Machine Learning models would be best to use for a Machine Learning task based on the properties of the data.
- Tune hyperparameters and use techniques like sampling and regularisation to improve model performance.
- Introduction to Machine Learning: Supervised Learning
- Unsupervised Algorithms in Machine Learning
- Introduction to Deep Learning