Machine Learning Algorithm 

The machine learning algorithm is the process by which the artificial intelligence system performs its task of predicting the output value from the given input data. Moreover, classification and regression are the two main processes involved with machine learning algorithms.

It is also considered the set of mathematical techniques through which an artificial intelligence system performs its tasks. These tasks include understanding important insights and patterns. And also predictions from input data the algorithm is trained on.

Any data science professional will feed the ML algorithm training data to learn from the data that will optimize the decision-making capabilities and create desired outcomes.

However, machine learning is a subset of computer science and artificial intelligence. ML has been expanded in the past few years along with other areas like deep learning algorithms for big and natural language processing for speech recognition.

How do Machine Learning Algorithm Works?

A data scientist will make the machine learning algorithm and direct it to examine particular variables within them to identify patterns and make predictions. The idea is to make the algorithm learn the data over time and on its own. Therefore, the more data it analyses, the better it will become at making relevant decisions without being explicitly programmed, just like humans would.

This training process is called as input data. The data produced by the algorithm is called output data. Data experts who build ML models must select the suitable algorithms to perform the tasks. For example, some algorithms are created for security, which will detect fraud in the organization. And also, some others are designed to help solve business issues like forecasting and regressions.

Types of Machine Learning Algorithm

1. Decision Tree
2. Logistic Regression
3. Linear Regression
4. K-means
5. Random Forest
6. Artificial Neural Network

Conclusion

In conclusion, machine learning algorithm is the subgroup of computer science and artificial intelligence. ML has been expanded in the past few years along with other areas like deep learning algorithms for big and natural language processing for speech recognition. Moreover, it is helpful in many places like health, business, computer vision, etc.