What is Machine Learning?

What is Machine Learning?

Machine Learning is the field of study that gives computers the capability to learn without being explicitly programmed. Currently, Machine learning, Data Science and Artificial Intelligence are some of the most trending topics in the tech world. Machine Learning is basically the study of how a machine or a program can automatically learn to make accurate predictions on the basis of past experiences. The basic objective of machine learning is to build algorithms that can receive input data and use different kinds of statistical analysis to predict an output while updating outputs as new data becomes available.

The classical definition of Machine Learning states that “A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E.”

Figure 1: Typical Diagram of A Machine Learning Program (Source: Internet)

Why Use Machine Learning?

Machine learning algorithms are often much more accurate than human crafted rules because they are data-driven. As it doesn’t require a human expert or programmer for a simple or complex task, it can be widely used in various fields. It has automatic methods to search for the hypotheses explaining data. It’s also cheap and flexible. So, we can apply to any learning task.

Applications of Machine Learning:

Machine Learning is everywhere. The possibility is that you are using it in one way or the other and you don’t even know about it. Machine learning algorithms are used in various applications such as –

  1. Face Recognition
  2. Email Spam Detection
  3. Malware Detection
  4. Robotics
  5. Recommender Systems
  6. Forecasting
  7. Vision and Language Processing
  8. Pattern Recognition
  9. Games
  10.  Fraud detection etc.

Machine Learning with Python

Python is a popular programming language used for web development (server-side), software development, statistics, system scripting, etc. Python has libraries that provide developers a platform to use optimized algorithms. One can implement popular machine learning techniques such as recommendation, classification, and clustering in python. It is necessary to have a brief introduction to machine learning before we move further.

Python has libraries like NumPy, SciPy, Scikit-Learn, Matplotlib which are used in data science and data analysis. They are also extensively used in machine learning algorithms.

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