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I think that they are fantastic. I attended Yale and Stanford and have worked at Honeywell,Oracle, and Arthur Andersen(Accenture) in the US. I have taken Big Data and Hadoop,NoSQL, Spark, Hadoop... Read More
I came to the platform with no experience and now I am knowledgeable in Machine Learning with Python. No easy thing I must say, the sessions are challenging and go to the depths. I looked at graduate... Read More
Time series forecasting has been one of the important area in data science, it is important to predict a variable associated with time elements such as sales, demand, revenue, profit etc. For logistic and supply chain companies, they need to know the exact inventory they need to stock for that they need to predict the demand for future.
Similarly, people in sales and marketing need to know how much order the customers are going to place so that they can manage their staff. Telecom companies should know how much manpower they need to prepare so that they can handle peak hour traffic etc. In various businesses, at least 5-10 areas where the variable of interest is associated with the time element.
Let’s look at few examples where we can apply various time series forecasting techniques.
In this machine learning project , you will predict the total travel time of taxi trips from their initial partial trajectories.
In this data science project, you will learn how to perform market basket analysis with the application of Apriori and FP growth algorithms based on the concept of association rule learning.
In this supervised learning machine learning project, you will predict the availability of a driver in a specific area by using multi step time series analysis.