Machine learning (ML) is a subset of artificial intelligence and involves the study of computer algorithms. It is extensively used to design and train computers using data to make them learn by themselves and perform critical tasks without any human intervention.
Considering the fact AI is future and it has created a huge demand for competent professionals, obtaining a credential in deep learning in which a subset of machine learning is important if you want to make a career out of it.
The write-up further highlights how machine learning works, its applications, examples, and how to start.
How does machine learning work?
Well, we know that machine learning is training computers to learn and perform the intended tasks. But, how does it work? Well, it is a five-step method.
- Gathering – It involves the feeding of data collected in different types, formats, and sources such as word documents, text files, and spreadsheets.
- Data preparation – It involves data extraction that had been fed to the machine. The data that makes sense to the machine is used for processing. Besides, it also involves inspecting undesirable and missing data.
- Training – In this step, the filtered data is divided into two parts. One part is used for training using an appropriate algorithm and the other is used for reference. The training data is used for creating the data model.
- Evaluation – This step involves testing the accuracy after the training.
- Feedback and re-evaluation – This step involves improvement in the performance of the machine based on feedback and re-evaluation.
Applications of machine learning
Today, machine learning is being used in different fields and industries. Let us take a glance at some of them.
- Insurance
- Online advertising
- Agriculture
- Banking
- Bioinformatics
- Computer networks
- Natural language processing
- Telecommunication
- User behavior analytics
As it is evident from the list that the interference of machine learning is prominent in almost every field, no surprise why it seems so promising as a career option. If you want to make a career out of it, you need to earn a credential in deep learning and machine learning.
Examples of machine learning
Mentioned below are some of the notable examples of machine learning.
Healthcare
The healthcare industry today heavily relies on machine learning. Huge datasets are being used to get crucial insights that aid healthcare professionals in planning and providing better care to the patients.
Speech recognition
Google Assistant, Siri, and Alexa allow you to do various things using your voice. These voice-based searches are some great examples of speech recognition that uses the concept of machine learning.
Financial services
BFSI industry is extensively using machine learning to predict and minimize the chances of financial frauds and understand customer’s spending patterns and credit habits to improve their experience.
How to start?
Now that you understand machine learning well, the next thing that you need to do is find a course that you can pursue. If you enroll at FORE, you get to learn machine learning and deep learning with python. Talking about python, it is a popular programming language that helps you build models for machine learning.
For detailed information about the course content, get in touch with us today@ 011-41242471/ 498.