Machine Learning Foundations

Solid machine learning foundations presented by a world leading expert. Full life cycle of machine learning development applied to enterprise-grade projects. It is based on the instructor’s book Intuitive Machine Learning. Includes Python coding, scientific computing, optimization algorithms, explainable AI and state-of-the-art methods favoring simplicity, scalability, reusability, replicability, fast implementation, and easy maintenance.

From data cleaning to model design, testing and feature selection, to great visualizations easy to “sell” to stakeholders and decision makers. We will cover topics across augmented data, generative and mixture models, big data, deep neural networks, image processing, machine learning in GPU, graph models, curve and shape fitting, taxonomy creation (NLP) and more. Numerous regression methods including logistic or Lasso are unified and presented under the same umbrella.