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Machine Learning
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Congratulations on taking a big step toward becoming a machine learning practitioner! In addition to working with the provided material, be sure to take advantage of all of the learning support available to you, including tips from other experts in machine learning.
Machine Learning is a way of taking data and turning it into insights. We use computer power to analyze examples from the past to build a model that can predict the result for new examples. We encounter machine learning models every day. For example, when Netflix recommends a show to you, they use a model based on what you and other users have watched to predict what you would like. When Amazon chooses a price for an item, they use a model based on how similar items have sold in the past. When your credit card company calls you because of suspicious activity, they use a model based on your past activity to recognize anomalous behavior.
Introduction to Machine Learning resources
A list of resources offered by various institutions from Stanford University to Google to Coursera. Some of these, such as the Stanford and Google courses, are offered for free, while others, such as Coursera, can be paid for either once or via a monthly subscription. If you want to learn Machine Learning, but have no idea where to start, feel free to look into them.
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