Python Machine Learning Course Outline
Our machine learning course provides an overview and hands-on practice. Course participants will be able to build, train, evaluate and deploy machine learning models with industry-specific data.
We recommend this course to anyone with a quantitative background who is getting started with machine learning. The course is suitable for practitioners and newcomers with a basic knowledge of calculus and statistics, and can be tailored to your needs.
- Overview of the pandas library for quick data manipulation.
- Visualizing and grouping data in pandas.
- Feature engineering and preprocessing.
- Univariate data analysis. Visual data quality.
- Machine Learning fundamentals. Overview of scikit-learn.
- Supervised Learning.
- Unsupervised Learning.
- Cross validation and model selection.
- Introduction to neural networks and deep learning.
- Convolutional neural networks for image processing.
- Recurrent neural networks for time series.
- Outlier detection with autoencoders.