Health care doesn't have a big data problem. It has a big data opportunity, thanks to artificial intelligence. Think about the number of inefficiencies in your daily life -- long lines, traffic jams, a reliance on "snail mail" for certain bills or communications. Those inefficiencies are inconvenient and annoying, yes, but they are usually not a matter of life and death. The need for productivity in health care is different.
Diabetes is one of deadliest diseases in the world. It is not only a disease but also a creator of different kinds of diseases like heart attack, blindness, kidney diseases, etc. The normal identifying process is that patients need to visit a diagnostic center, consult their doctor, and sit tight for a day or more to get their reports. Moreover, every time they want to get their diagnosis report, they have to waste their money in vain. But with the rise of Machine Learning approaches we have the ability to find a solution to this issue, we have developed a system using data mining which has the ability to predict whether the patient has diabetes or not.
For breakfast he requests wheat germ, organic honey and tiger's milk - food in 1973 thought to be healthy. The futuristic doctors reply: "You mean there was no deep fat? No steak or cream pies or... hot fudge?" and "Those were thought to be unhealthy... precisely the opposite of what we now know to be true." A recent article in the Wall Street Journal entitled "The Questionable Link Between Saturated Fat and Heart Disease" details scientific malpractice in research about what food is healthy or not. For over fifty years the scientific consensus was that fat - both saturated or not - is a "cause" of obesity, heart disease, and other chronic diseases.
Big data analytics are driving innovations in scientific research, digital marketing, policy-making and much more. Matplotlib offers simple but powerful plotting interface, versatile plot types and robust customization.Matplotlib 2.x By Example illustrates the methods and applications of various plot types through real world examples. It begins by giving readers the basic know-how on how to create and customize plots by Matplotlib. It further covers how to plot different types of economic data in the form of 2D and 3D graphs, which give insights from a deluge of data from public repositories, such as Quandl Finance. You will learn to visualize geographical data on maps and implement interactive charts.By the end of this video, you will become well versed with Matplotlib in your day-to-day work to perform advanced data visualization.
We live in a world of health data. With fitness trackers, electronic health records, sleep monitoring and countless other ways to track and measure our health, we've entered an exciting era in which the flow of data to our doctors, pharmacists and other care providers is revolutionizing how and how fast health care services are delivered. It's also given consumers windows into their own health that was just a dream 20, 10, even five years ago. Not long ago, we really only got a picture of our health once a year when we went to our doctor for an annual check-up. We'd get blood drawn, blood pressure, weight and other vital statistics were taken, and our doctor would declare us healthy or give us things to work on.