you have a complex problem involving a large amount of data and lots of variables, but no existing formula or equation. you know that machine learning would be the best approach—but you’ve never used it before. how do you deal with data that’s messy, incomplete, or in a variety of formats? what specialized knowledge is required to train the algorithm? how do you choose the right model for the data?
sound daunting? don’t be discouraged. remember that trial and error is at the core of machine learning—if one approach or algorithm doesn’t work, you simply try another. but a systematic workflow will help you get off to a smooth start.
read this ebook to go step by step from the basics to advanced techniques and algorithms. in this interactive ebook, you will find:
- clear definitions of key concepts in machine learning
- outlined steps of a systematic workflow
- an overview of key algorithms for supervised and unsupervised learning