Applied Machine Learning: Foundations
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Description
This course is the first part of the Applied Machine Learning series, focusing on the foundations of machine learning. It provides a pragmatic approach to solving machine learning problems, from exploratory data analysis to model evaluation. The course does not focus on any specific algorithm but provides the tools to efficiently solve a wide range of machine learning problems, making it a valuable resource for anyone looking to delve into the field of machine learning.
Learning Objectives
- Understanding what is machine learning.
- Differentiating Machine Learning, Deep Learning, and Artificial Intelligence.
- Handling common challenges in Machine Learning.
- Plotting continuous and categorical features.
- Cleaning continuous and categorical data.
- Measuring success in Machine Learning.
- Identifying overfitting and underfitting.
- Tuning hyperparameters.
- Evaluating a model.