Computers have played a very big role in our lives in the past 2 decades. In the past decade there have been numerous improvements in technology, thus Large Scale Machine Learning became feasible for companies. Now Machine Learning is practically in every part of our lives. In this post you will learn about all the applications of Machine Learning in daily life
Hey Guys, This is Manas from csopensource.com – “Your one stop destination for everything Computer Science”.
I know that many of you are excited about learning the fundamentals of Machine Learning and want to start at the earliest, but I am making you familiar with all the things that you need to know before learning to code ML Apps. Believe it or not! Machine Learning is not about writing code, its about understanding how the model works and understanding all the core concepts well enough! Coding comes later. Theory is always first!
Computers have grown a lot in computational power since the 70’s. Computers are becoming more capable day by day. One of Intel’s founders Gordon Moore had also stated that the number of transistors on a dense integrated circuit doubles every two years. This has been referred to as the Moore’s Law. This law just shows that the computational power increases with time. At the present stage this observation is no longer applicable as we are not seeing a massive increase in transistor count, which arguably means that computational power is getting close to its peak. This suggests that there is a certain limit on how much computation a computer can handle within a reasonable amount of time. Machine Learning can help in optimizing the instructions given to a computer in order to increase the efficiency of the work done by it!
There are certain problems that are too difficult for a traditional computer to solve with hard-coded instructions, like for example predicting if a patient has cancer, if the patient has a chance of getting coronary heart disease etc. These kinds of problems have multiple dimensions and multiple outcomes, mainly probabilistic. There are also certain cases when a developer knows the input and the desired output. In this case if Machine Learning is used correctly, the computer can map the connections between the input and output all by itself. This saves a lot of time for the Developer. ML can also help the Scientific Community and also various indie scientists in predicting the outcomes of certain tests that they want to conduct.
Machine Learning encloses a lot of topics from Mathematics, Physics, Statistics and Geometry. Machine Learning models are classified into two categories: Supervised & Unsupervised Machine Learning.
Some Practical Applications of Machine Learning
- Computer Vision, this is the ability given to a computer to understand what is being shown to it.
- Virtual Personal Assistants, Virtual Assistants such as Google Assistant, Microsoft’s Cortana, Amazon’s Alexa and Siri from Apple are all based on Machine Learning.
- Predictions while commuting, Google Maps uses this technique along with GPS to predict the traffic status of a place.
- Personalized Social Media Content, Using Machine Learning based on the pictures you have liked in the past, Social Sites such as YouTube, Facebook, Instagram, Twitter etc. present pictures or advertisements which you may find interesting
- Spam and Malware Filtering, e-mails generally contain a lot of spam messages as well as viruses using Machine Learning these kinds of data can be filtered out
- Chat-bots, you may have seen in many places such as Amazon and other sites you can get to chat with a bot for customer support! Natural Language Processing(NLP) is used to train these chatbots.
- Optimized Search Results, sites like google create personalized advertisements using Google AdSense based on your interests. It also enhances your search experience as you are getting content based on what you like.
- Disease prediction, Machine Learning can help in predicting various types of diseases beforehand. This can give some valuable time for the patient to receive critical treatment.
- Others, Machine Learning is a vast field and has its roots almost everywhere!
So guys, according to me these were a few detailed descriptive sentences about what are the practical applications of Machine Learning. That is all for this blog, see you soon! In the next blog we will be starting with the first form of Supervised Learning, “Classification”. Until then, enjoy Deep Learning!