Moving towards optimized business solution with Prescriptive Analytics

Moving towards optimized business solution with Prescriptive Analytics

BI technology has grown in this era of information intelligence and still emerging with new and advanced solutions. One of the most promising approaches in the BI domain is prescriptive analytics. To understand the concept of prescriptive analytics, firstly one should understand and relate it with descriptive and predictive analytics since prescriptive analytics is closely related to both of them. While descriptive analytics aims to stipulate insight into what is already occurred and predictive analytics peeps into model and forecast…

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Beauty of Python: Zen says it all

Beauty of Python: Zen says it all

It has been a long time that Pythoneer Tim Peters briefly wrote the guiding principles for Python design into 20 aphorisms. Let’s revisit them in simplified way. After all, your choice of Python as a technology is all about simplifying tough things! 1.Beautiful is better than ugly Write simple expressions. Programs should be human readable and understandable. So keep it consistent. It says that “don’t make me think much”. Example: Logical operators – Use of and, or instead of &&,…

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IOT Analytics: Adding value to the business

IOT Analytics: Adding value to the business

Have you heard of smart devices? Yes, obviously and most of you will state smartphone as the popular example. Have you heard of smart appliances (such as refrigerators, ACs and what not?). Let me tell you that IoT is not just smart refrigerators, it is more than that. IoT (Internet of Things) brings insights in business applications by managing and analyzing data. IoT (Internet of Things) seems like customer fantasy came true, customer will have the facility to switch off…

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Exploratory Data Analysis: First milestone of data analysis

Exploratory Data Analysis: First milestone of data analysis

In statistics, exploratory data analysis (EDA) is a technique that analyze data to recapitulate their major features, frequently with visual approaches. Its is an initial step of data anlysis from experiment. Primarily EDA is for sighting what the data can express beyond the formal modeling or hypothesis testing job. EDA is different from initial data analysis (IDA) which emphases on glancing assumptions needed for model fitting and hypothesis testing, and managing missing values and making transformations of variables as required….

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Machine Learning Fundamentals

Machine Learning Fundamentals

Machine Learning is motivating computing machines (chill, I am talking about computers) to program themselves. It is type of artificial intelligence. If program writing is considered as an automation, then machine learning is automating the procedure of automation. Composing programming is the bottleneck, we don’t have enough great engineers. Give the information a chance to take the necessary steps rather than individuals. Machine learning is the best approach to make programming adaptable. Machine learning is like farming or gardening. Assume…

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