Machine Learning Processes And Scenarios


Introduction

Things in machine learning are repeated over and over and hence machine learning is iterative in nature. Therefore, to know machine learning, one has to understand the machine learning process. The machine learning process is a bit tricky and challenging. It is very rare that we find the machine learning process easy. The reason for it being so complex is very clear – a large amount of complex data is involved in this process and out of which we try to find out meaningful predictive patterns and model. That’s why, as I mentioned in my last article that this is dealt by data scientists who are actually specialists in this space. In my last article, I also mentioned how rewarding a machine learning process could be. The benefits out of this process could be outstanding, but we should also keep in mind that the process may not always succeed but can fail, but that’s too rare. Let’s focus on the processes and scenarios used in Machine learning in this article.

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Introduction to Machine Learning


Introduction

Why Machine Learning? Why would you want to understand Machine Learning? How does it matter to your life? If you’re not a master of it, why do you at least need to understand the basics of Machine Learning? The answer to all these questions is very simple. It’s because Machine Learning on a day to day basis is becoming bigger and it is knowingly or unknowingly part of our life and so it is important to know what it is. We’ll try to answer all the basic questions related to machine learning in this and the following articles on Machine Learning and at least know what Machine learning is and what could be achieved with Machine Learning.

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