The insurance company I work for has a computationally intensive process to estimate future earnings based on tables of assumptions regarding price and probability of cancelation. I would like to train a model to approximate this process. I have tried a number of models, including xgboost and various configurations of neutral networks. The problem is that even when the model shows good performance on both training and test sets, it doesn't succeed in estimating the effect of a change in …
I was asked this in an interview for a Data Scientist position: Lets say Holland and Barret came to you and said they'd like to increase their sales and revenue. How will you go about it? My answer wasn't hitting the mark or touching the points the interviewer was looking for. How to go about answering this?
I have read lot of blogs\article on how different type of industries are using Big Data Analytic. But most of these article fails to mention What kinda data these companies used. What was the size of the data What kinda of tools technologies they used to process the data What was the problem they were facing and how the insight they got the data helped them to resolve the issue. How they selected the tool\technology to suit their need. What …
I just started learning data science. I have gone through some of the courses in coursera & udemy, now i want to practice what i have learned. What i want to know is from where can i get the Use cases (linear regression & multiple linear regression) so that i could practice
I recently found this use cases on Kaggle for Data Science and Data Analytics. Data Science Use Cases However, I am curious to find examples and case studies of real reports from other professionals in some of those use cases on the link. Including hypothesis, testing, reports, conclusions (and maybe also the datasets they have used) Do you have any kind of those reports to share? I am aware of the difficulty to share this kind of details and this …
It is a real world use case. For example, a route from place A to place B can be different series of lat, lng points - the different trips though they are exactly the same sequence from Street x and then Road y then High way z. The differences are the locations are reported in different time (for example each trip reports the location 1 minute) and the Vehicles appear in the different lane of the same street. So, do …
The most popular use case seem to be recommender systems of different kinds (such as recommending shopping items, users in social networks etc.). But what are other typical data science applications, which may be used in a different verticals? For example: customer churn prediction with machine learning, evaluating customer lifetime value, sales forecasting.