EP 3. APPROACHES TO MACHINE LEARNING(PART 2):
EP3 APPROACHES TO ML(PART 2): In the last post we have seen how supervised learning performs to get the output in 2 ways i.e in continuous valued output and discrete valued output. Now without any delay let's get started with Unsupervised learning. Unsupervised learning is best suited when the problem requires a massive amount of data which is unlabeled. This data is actually un readeable or not really intresting to see. For example , Social media applicants such as twitter,Instagram,facebook and many social media applicants have lot amounts of unnamed data. By applying unsupervised machine learning algorithms, the system will learn itself from its own mistakes through many attemps and use cases. Some of the intresting examples where we apply machine learning algorithms is Self driving cars and also drones. In Unsupervised machine learning we actually hear a lot about clustering. When you came across google news, You actually find the same data which is published by many