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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.
Using this Kaggle dataset, you will explore which type of employees make less or more money, or which employees get normal pay hikes and promotions.
Machine Learning Project - Work with KKBOX's Music Recommendation System dataset to build the best music recommendation engine.
In this machine learning resume parser example we use the popular Spacy NLP python library for OCR and text classification.