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Michael Grogan is a machine learning consultant and educator from Ireland. He has a particular interest in time series analysis using both Python and R, and the use of such analysis in generating business intelligence solutions.
The rest of his stack includes AWS (Cloud Practitioner Certified), Docker, Linux, MySQL, PostgreSQL, Shiny.
Michael is also a regular speaker at various data science seminars, and has delivered talks at venues including Big Data Vilnius, Nordic Data Science and Machine Learning Summit Stockholm, University College Cork R-Users, Trinity College Dublin, and World Machine Learning Summit Dublin.
Predicting Hotel Cancellations with Machine Learning
Hotel cancellations can cause issues for many businesses in the industry. Not only do cancellations result in lost revenue, but this can also cause difficulty in coordinating bookings and adjusting revenue management practices.
This session explores how machine learning techniques can be used to predict hotel cancellations. Firstly, data manipulation techniques with pandas are employed to effectively process over 20,000 customer entries. Feature selection tools such as the Extra Trees Classifier are then used to pinpoint the main drivers of hotel cancellations. The use of logistic regressions, support vector machines, and SARIMA are employed for prediction purposes, and extensive visualisations with pyplot are also generated to illustrate cancellation trends across different time periods.