Everyone knows that technology is the future, with areas such as machine learning and artificial intelligence (AI) leading the way. So how can you become part of this world to become a machine learning expert?
A branch of computer science, machine learning is a relation of artificial intelligence (AI), and relates to the way that data and algorithms can imitate the way humans learn and think. Essentially, machine learning enables computers to ‘learn’ without a specific program telling them what to do.
Machine learning is already used widely across the world, probably without you realizing. When you type out a text message on your phone, the predictive text function is powered by machine learning. Chatbots that can help you instantly on a website instead of a human in customer service are also run by machine learning. Machine learning is also crucial in language translation apps, and helps to make great suggestions when you’re shopping on Amazon or browsing Netflix.
Most AI systems that are in use have machine learning elements to them. The idea of AI is that systems can perform complex, multi-tiered tasks that currently only humans can do – i.e. making computers ‘intelligent’. In recent years, machine learning has gone from being a niche to something that spans industries. Two thirds of companies now use some form of machine learning for their business, with most companies planning to use machine learning in the future.
Creating a new machine learning process requires several steps. The first necessity is having access to plenty of data to help train the machine. Data can be in the form of text, numbers or even imagery. The general rule that applies to machine learning is that the more data you have, the better the program. There are different machine learning models, and you then need to choose one of these models that will be the most relevant to your data and project. You can supply the data to this model, which will then run itself while learning, identifying patterns, and eventually making predictions. Human programmers are often needed to refine parts of the process to enable the machine to learn better.
Enabling a machine to learn in this way means that more businesses can automate key parts of their processes, and problems can be solved. The machine learning field is growing rapidly, making this an important area for people to learn and gain expertise in. If you’re keen to become a machine learning expert, here’s what you need to do.
1. Read
The world of machine learning is exciting but complex. If you think you’d like to work in the field, it’s important to read as much about it as you can. Read a machine learning blog, the latest research from universities on machine learning, and technology media publications to learn all you can. If you’re still excited by it when you’ve read widely on the subject, it’s time to gain some skills.
2. Learn Mathematics
The basis of machine learning is rooted in mathematics, so it is essential to gain some strong mathematical skills. The sub-topics of mathematics you need to know well include statistics, probability, algebra and calculus. How you learn depends on what stage of your education you are at, but there are plenty of websites, reading materials and online courses that can help you get up to scratch in this area.
3. Understand Programming
Any computer science discipline such as machine learning requires you to know about programming and data analysis. Some of the most popular tools to use are Python and R, so learn how to use these. Again, there are plenty of online courses and ‘how to’ guides on these topics, so build up your knowledge and confidence gradually. You can set yourself tests and tasks, or follow some online guidance to help build up your skillset.
4. Do Some Projects
Once you understand the foundations of machine learning and programming, you’re ready to test out your knowledge on some actual data. You could either follow a machine learning process you find online to see if you can do it for yourself, or you can use your own data set and try something out for yourself. Choosing a topic you are really interested in can truly help, as you will have a vested interest in the results, as well as an in-built understanding of what you can expect from the machine learning results.
5. Plan Your Future
If you’ve self-taught yourself to this point, the next step is to decide what to do next. There are specific college and university courses in machine learning that you could embark on to progress your learning. This route will also enable you to gain opportunities to research areas of machine learning that have potential. If you’d prefer to go straight into work, contact some tech and AI companies to see if you can get some work experience. You may even have a shot at getting a junior position!