Machine Learning and Artificial Intelligence are in the headlines everywhere today. Those who are learning how to make Machines that exhibit Intelligence today are tomorrow going to lead the next technological revolution. Learn about the latest cutting-edge research and stand a chance to disrupt almost all industries through their skill sets.
Machine Learning Definition
What is Machine Learning? Machine Learning is an application of Artificial Intelligence (AI) that provides systems the ability to learn from their experiences and make predictions based on past data without being explicitly programmed. The goal of artificial intelligence is to create a machine that can imitate a human personality and to do that it needs learning capabilities. However, it’s more than just about learning. It is also about knowledge, reasoning, representation and even things that abstract thinking. On the other machine learning hand is solely focused on writing software that can learn from past experience. Applications of Machine learning is more close to data mining and statistics than it is to Artificial Intelligence.
Machine Learning can be split into Three Categories –
Supervised Learning (Trained me) – Where you teach and train the machine using data which already has labels.
Unsupervised Learning (I am self-sufficient) – Where you teach and train the machine using a data set that doesn’t have labels.
Reinforcement Learning (Hit & Trial) – It is similar to unsupervised learning in that the training data is unlabeled.
What is Machine Learning Algorithms?
Our ability to learn and get better at tasks through experience is part of being human. When we are born we know almost nothing and can do almost nothing for ourselves. But soon we are learning we are becoming more capable every day but did you know that computers can do the same. Machine learning brings together statistics computer science to enable computers to how to learn to do a given task without being programmed to do so. Just as your brain uses the experience to improve a task so can a computer.
Let’s say you need a computer that tells the difference between a picture of a dog and a picture of a cat. You could begin by feeding it images and telling it which one is a dog and which one is a cat. A computer programmed to learn will seek statistical patterns within the data that will enable it to recognize a cat or a dog in the future. It might figure out on its own that cats have shorter noses and dogs come in the larger variety of sizes. And then represent that information numerically organizing in space. But crucially it’s a computer, not the programmer to identify those patterns and establishes the algorithms by which future data will be shorted.
One example is of the simple yet highly effective algorithm is to find the optimal line separating cats from dogs when the computer sees a new picture it checks which side of the line it falls on then says either cat or dog. Machine Learning is already widely applied. It’s the technology behind facial recognition, text to speech recognition, the spam filter on your inbox & online shopping. People are doing research on Machine Learning to combine statistics and computer science to build algorithms that can solve complex problems more effectively, using less computing power.
Machine Learning Examples
There are many successful companies which are using Machine Learning to reach the right targets. They take a market and completely changed it. They are often differentiated by Intelligent Applications using Machine Learning and its core. For example, Amazon really disrupted the retail market by bringing in products recommendations into the website. We saw Google disrupting the advertising market by right targeting audience with machine learning to figure out what people would click on.
On the other hand Netflix the movie distribution company, really changed how movies are seen. Now we don’t go to a shop and rent movies anymore. We go to the web and stream data. And at the core, Netflix has a recommender system that helped to find the movies. Pandora is a music streaming & automated music recommendation system where I can find music that I would like to listen in the morning or when I’m going to sleep. They are using Machine Learning for recommending music to users. You see Facebook connecting you with people who you might want to be friend with. Uber optimizing how to connect drivers with people in real-time with the help of Intelligence.
There are thousands of real-time examples around us. Machine Learning is also using in IoT Applications to collect data from the IoT devices. Want to learn in-depth about Machine Learning and it’s applications in real-time click here