What this learning path covers

Module 1, Python Machine Learning, discusses the essential machine algorithms for classification and provides practical examples using scikit-learn. It teaches you to prepare variables of different types and also speaks about polynomial regression and tree-based approaches. This module focuses on open source Python library that allows us to utilize multiple cores of modern GPUs.

Module 2, Designing Machine Learning Systems with Python, acquaints you with large library of packages for machine learning tasks. It introduces broad topics such as big data, data properties, data sources, and data processing .You will further explore models that form the foundation of many advanced nonlinear techniques. This module will help you in understanding model selection and parameter tuning techniques that could help in various case studies.

Module 3, Advanced Machine Learning with Python, helps you to build your skill with deep architectures by using stacked denoising autoencoders. This module is a blend of semi-supervised learning techniques, RBM and DBN algorithms .Further this focuses on tools and techniques which will help in making consistent working process.