We live in a start of revolutionized era due to development of data analytics, large computing power, and cloud computing. Machine learning will definitely have a huge role there and the brains behind Machine Learning is based on algorithms. This article covers 10 most popular Machine Learning Algorithms which uses currently.
KNN can easily be mapped to our real lives. If you want to learn about a person, of whom you have no information, you might like to find out about his close friends and the circles he moves in and gain access to his/her information! It is a type of unsupervised algorithm which solves the clustering problem. Its procedure follows a simple and easy way to classify a given data set through a certain number of clusters (assume k clusters). Data points inside a cluster are homogeneous and heterogeneous to peer groups. Remember figuring out shapes from ink blots?
Google's self-driving cars and robots get a lot of press, but the company's real future is in machine learning, the technology that enables computers to get smarter and more personal. We are probably living in the most defining period of human history. The period when computing moved from large mainframes to PCs to cloud. But what makes it defining is not what has happened, but what is coming our way in years to come. What makes this period exciting for some one like me is the democratization of the tools and techniques, which followed the boost in computing. Today, as a data scientist, I can build data crunching machines with complex algorithms for a few dollors per hour. I had my dark days and nights.
Modern advancements in Artificial Intelligence (AI) are set to change our world for the better. These developments have largely been made possible due to technologies such as cloud sharing, data analytics, blockchain, and improved computing power. These technologies have significantly improved machine learning, the main cause driver behind AI advancements. Machine learning is probably the most important component of developing Artificial Intelligence. The process of machine learning involves running repeated simulations on a computer, recording the results, and then running new tests based on the previous outcomes.