Success With Machine Learning Projects in Python

Success With Machine Learning Projects in Python

In this article, we will give you a sense of the applications for machine learning and explain why Python is a perfect choice for getting started.

What does it mean for a machine to learn? In a way, machines learn just like humans. They infer patterns from data through a combination of experience and instruction.

In this article, we will give you a sense of the applications for machine learning and explain why Python is a perfect choice for getting started.

We will discuss concepts central to machine learning and walk you through a simple example of a machine-learning algorithm in Python.

What is Machine Learning?

Machine-learning algorithms are mathematical models that predict something—a category, for example, or a continuous value. To arrive at a prediction, a machine-learning model transforms its input using various parameters that it infers from the data.

This is the learning part of the process, and it happens iteratively: After seeing the data, the model makes its guess and is then told, by means of a loss function, how far off it was from the desired output.

In the next iteration, the model tries to improve its predictions by adjusting its parameters, and after a number of iterations, we can assess our trained model using an evaluation function. If we find that the results are satisfactory, then the model is ready to make predictions about new, never-before-seen datapoints.

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