My name is Özgür Akbelen. I graduated from Boğaziçi University Management Information Systems in 2017. Upon my graduation I have been working in CRM field since 4 years. I started my career as assistant CRM specialist in Sony Eurasia in 2018. After almost 3 years of working at Sony I had an opportunity to work as CRM Manager at Storytel. Since February 2021 I continue my career with this role.
Customer segmentation has always been one of the most attractive duties I was involved in. I participated in creating different segments based on different goals mostly by using SQL and different marketing cloud platforms such as Salesforce and Braze. After working closely with data branches I noticed that I want to go deeper with data increase my knowledge in data science as I noticed that part of my job could be something that I would like to focus more and spend more time with. Considering my background and my future goals for my career I believe this program will broaden my horizon in data field and bring new opportunities. Please click here for my Linkedin.
R is one of the popular languages in data science ecosystem. It is mainly designed for statistical computing and graphics and thus it eases implementation of statistical techniques, which makes it excellent choice for machine learning tasks. In this article a random forest mode is createdl to solve a machine learning problem: churn prediction. Please click here for more.
We can let computer create the clusters of personas thanks to unsupervised classification, which lets computers decide how to use the values and characteristics of the data. Clustering is one of the examples unsupervised classification. There are lots of different clustering techniques used depending on the approaches used to solve the problem. This article gives more info on ways to organize data by using clusters along with theoretical knowledge and practices for both K-means clustering and agglomerative hierarchical clustering. Please click here for more.
In this post author starts with explaining the importance of outliers and gives it to the reader with showing the differences of a linear regression study with and without outliers. Blog is also enriched with code pieces in details along with graphical displays along the way from detection to treatment of outliers. Please click here for more.