O’Reilly – Dealing With Real-World Data

O’Reilly – Dealing With Real-World Data
English | Size: 217.11 MB
Category: Tutorial

This course covers a subject central to the practice of data science and machine learning: the tricky and often overlooked problem of how to deal with real-world data. It provides an overview of the things data scientists think about when gaining access to a data set. You’ll learn about data types, data exploration, the curse of dimensionality, PCA, model evaluation, and more, in this pragmatic introduction to the terminology and concepts surrounding data and machine learning. Learners with a basic working knowledge of mathematics will be able to enjoy the course and immediately start working on machine learning problems.

• Learn to handle the many types of data used in real-world machine learning projects
• Explore topics like data exploration, the curse of dimensionality, and PCA
• Understand how to evaluate models and why this is important
• Learn how to use – and enjoy free access to – the SherlockML data science platform
• Develop the skills required for the machine learning job market where demand outstrips supply

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