What is machine learning ?
Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.
How machine learning works ?
A Decision Process
In general, machine learning algorithms are used to make a prediction or classification. Based on some input data, which can be labelled or unlabelled, your algorithm will produce an estimate about a pattern in the data.
An Error Function
An error function evaluates the prediction of the model. If there are known examples, an error function can make a comparison to assess the accuracy of the model.
A Model Optimization Process
If the model can fit better to the data points in the training set, then weights are adjusted to reduce the discrepancy between the known example and the model estimate. The algorithm will repeat this “evaluate and optimize” process, updating weights autonomously until a threshold of accuracy has been met.
Why is Machine Learning Important ?
Machine learning is growing in importance due to increasingly enormous volumes and variety of data, the access and affordability of computational power, and the availability of high speed Internet. These digital transformation factors make it possible for one to rapidly and automatically develop models that can quickly and accurately analyze extraordinarily large and complex data sets.
There are a multitude of use cases that machine learning can be applied to in order to cut costs, mitigate risks, and improve overall quality of life including recommending products/services, detecting cybersecurity breaches, and enabling self-driving cars. With greater access to data and computation power, machine learning is becoming more ubiquitous every day and will soon be integrated into many facets of human life.