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Role Of Business Analytics In The Food Industry by imexpert109 Some years before there was no such big demand for business analysts in the food industry. And let me tell you no one will feel surprised to hear this, all because the food industry was growing at a pace of a snail in those days. Which means, with passing days, it was expanding a little. But many many thanks to online marketing, for which the food sectors have grown (rapidly) than ever before. Slowly ordering on the online platform came into existence, and believe me or not, but the truth is it has changed the world of the food industry like never before. And today, there are so many food manufacturing companies, that were opened and well-established with lots of royalties and profits in the market. If you stay in Mumbai and looking forward to a career in business analysts in Mumbai in the food sector industry, then this article is for you, without any doubt. Have you ever thought in the wildest dream, that the food industries would be turning into MNCs? 304, 3rd Floor, Pratibha Building.
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Pin on Projects to Try Explore more ideas with a Pinterest account Sign up to see more Continue with Facebook Continue with Google By continuing, you agree to Pinterest's Terms of Service, Privacy Policy Already a member? Naive Bayes Algorithms In Data Science by imexpert109 Naive Bayes Algorithms In Data Science Naive Bayes Algorithms is a very important topic in data science that is based on Bayes theorem. It’s a must known technic for every data scientist professionals in today’s date. Naive Bayes algorithm is based on Baye’s Theorem of probability with an assumption of independence among predictors. To be precise Naive Bayers model is very easy to build and very useful for large datasets. How naive Bayes Algorithm works? Here are the three most important steps for the classification of Bayes theorem and widely used for classification of data sets. Step 1 The first and foremost step in the Bayes method is converting the data into the frequency table, that we have done in 6 or 7th grade if I am not wrong. Step 2 Create the likelihood table by finding the probabilities. Step 3 After the finish of the first two processes, you have all the required data with you. Pros and cons of Naive Bayesian Theorem The pros or the positive sides of the Naive Bayesian Theorem.
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