Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed. The name Machine Learning was coined in 1959 by Arthur Samuel.
Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to perform the task. Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or infeasible to develop conventional algorithms to perform the task.
What is ML?
Machine learning is a branch of computer science that involves the study of algorithms that learn from experience. It has been proven to be one of the most powerful tools in the field, and it is also one of the most popular topics among students. There are several reasons for this, but the main reason is that machine learning can help solve many problems in real life.
While there are a number of different types of machine learning, it's important to note that all of them are based on the idea that computers should be able to learn new things. They do this by studying their environment, which can include everything from your surroundings to what you're typing on your keyboard.
One type of machine learning algorithm is called a neural network, which is basically a set of mathematical equations used to model relationships between variables. These networks can be used to predict future events or even detect patterns in data sets that may not have been noticed by humans. Another type of machine learning is called supervised learning, where programs try to predict future outcomes based on past observations. This can be very helpful in analyzing trends over time or trying to find patterns in financial markets.
A third type of machine learning involves using artificial intelligence (AI) systems such as Google's DeepMind project and IBM's Watson supercomputer.
Programming used in Machine Learning
Python is the most popular programming language used in the field of machine learning today. It's a powerful, high level language which is relatively easy to learn and provides several useful libraries that make it ideal for using machine learning algorithms efficiently. The flexibility and simplicity of the language makes it an excellent choice for people who are just getting started with machine learning.
R is another language which has been growing in popularity among data scientists. It has a lot of visualizations, statistical analysis and packages available for use. R also comes with many useful packages that can improve your efficiency in certain areas such as ggplot2 for making visualizations or dplyr which is used to manipulate data sets quickly. The only downside to this is that it might take some time before you get familiar enough with them so if you want something more straightforward then Python would be better suited to you. However if need those features then R is definitely worth checking out!
JavaScript is another popular programming language used by developers who work on front-end apps or websites; however there are also some libraries for machine learning too! Tensorflow.js allows developers to train models right inside their web browser without having any knowledge about how to do so beforehand (this means no need for an expensive GPU). It also