Machine learning is about teaching computers how to learn from data to make decisions or predictions. For true machine learning, the computer must be able to learn to identify patterns without being explicitly programmed to.
Machine Badass(NOT Machine Learning)

It sits at the intersection of statistics and computer science, yet it can wear many different masks. You may also hear it labeled several other names or buzz words:
Data Science, Big Data, Artificial Intelligence, Predictive Analytics, Computational Statistics, Data Mining, Etc…
While machine learning does heavily overlap with those fields, it shouldn’t be crudely lumped together with them. For example, machine learning is one tool for data science (albeit an essential one). It’s also one use of infrastructure that can handle big data.
Here are some examples:
Supervised Learning – Your email provider kindly places that sketchy email from the “Nigerian prince with $50,000 to deposit into an overseas bank account” into the spam folder.
Unsupervised Learning – Marketing firms “kindly” use hundreds of behavior and demographic indicators to segment customers into targeted offer groups.
Reinforcement Learning – A computer and camera within a self-driving car interact with the road and other cars to learn how to navigate a city.


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