QuickDataScience | Quick & Easy Data Science

  Microsoft Power BI, a name that we all have heard a lot, is also quite famous in the field of Data Science. So, let's look at each aspect of it, including What it is, Why to use it, Who should use it and How to use it? What is Power BI? The first question that comes to mind is What is Power BI? Before we begin, let's see the Official definition of Power BI, Power Business Intelligence.  Microsoft defines it as:-  Power BI is a collection of software services, apps, and connectors that work together to turn your unrelated sources of data into coherent, visually immersive, and interactive insights. Your data may be an Excel spreadsheet or a collection of cloud-based and on-premises hybrid data warehouses. Power BI lets you easily connect to your data sources, visualize and discover what's important, and share that with anyone or everyone you want. Wikipedia defines it as:-  Power BI is an interactive data visualization software product developed by Microsoft with a primary

The first question that comes to mind is What is Digital Twin? and How is it related to Data Science and Medicines that we are studying here.  Don't worry we are going to start our post from this point only. What is Digital Twin? As the name suggests, Digital Twin is something related to Twin or a copy of something with a digital presence, or Virtual Presence. So, now the question is What is this "something" of which we create a copy? This "Something" can be anything process, plant, factory, human, machine etc. which is not well defined and might require multiple rounds of mix and match setups to get to the desired/maximum efficiency. These repeated steps not only take a lot of time but also a huge amount of money is also involved in the whole process. Also, there is an uncertainty that the process would succeed or not and how much more time will be required to get the final version.  Let's take a small example to understand the whole concept of the Digital

  Machine Learning is an essential term in the field of Data Science. We all have read and worked with different algorithms and might have also created many models for our projects. Today, I would like to introduce you to a new way of Machine Learning -- Online Machine Learning.  What it is?  Wait..!! I recently deployed my model over the server. Isn't it Online? Yes, your doubt is absolutely right. You might have deployed your model but it might not be learning online, and a model that can learn and train itself after being deployed is considered Online.  So What..!!! My model does it, I have configured it to learn about the new data periodically.  Great... that you have deployed such a model and I do hope that it's working fine, but sorry to say that's still not What we call Online. Then What do you call Online Machine Learning?? Enough of going round and round. Get to the point. Yes yes, just a second I will explain everything about it in some time but before that, I wou