BLOG ON MACHINE LEARNING,AI AND DATA SCIENCE!!GET STARTED!!

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...

  EP2. Approaches to Machine Learning: Today Lets get started with the approaches in ML. Machine Learning techniques are required to improve the accuracy of predictive models. There are actually different techniques used on different data and analysis stuff. SUPERVISED LEARNING: Supervised Learning typically starts with a well-addressed data and a certain understanding of how the data is classified. We actually give the well-structured data and apply machine learning algorithm we will get the output. So indirectly, we are telling the machine how the output will be like and what should we get actually from that. We actually tell the machine how to get the predictions for us.  The above picture represents the supervised learning. There are 2 types of Supervised Learning: 1>CLASSIFICATION     2>REGRESSION For example when you consider a patient is to verify if he is actually suffering from cancer or not: we actually use the classification tech...

EP 1.   INTRODUCTION TO MACHINE LEARNING Hey without any delay lets get started! Machine Learning(ML),Artificial intelligence, Cognitive computing, Data science are the evolving technologies in every field across the world and they are the certainly the next generation and today's world as well. While many will be thinking where we gonna use these intelligent technologies but its everywhere around us, for example, we use the phone all the time, Spamming emails that we hate to see and unsubscribe them, etc. So while I gonna explain one example of machine learning where we actually can get the definition of machine learning i.e spamming emails and when we spam the app notifications like Flipkart ETC so when we actually tell the computer about our desired needs and its  gonna divide the emails into 2 parts where it distinguishes from useful emails and spam emails. So indirectly we are giving the information to the computer to perform our desired tasks wit...

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