Restaurant Revenue Prediction - Regression problem
Predict annual restaurant sales based on objective measurements Kaggle : https://www.kaggle.com/c/restaurant-revenue-prediction Problem Statement: With over 1,200 quick service restaurants across the globe, TFI is the company behind some of the world's most well-known brands: Burger King, Sbarro, Popeyes, Usta Donerci, and Arby’s. They employ over 20,000 people in Europe and Asia and make significant daily investments in developing new restaurant sites.
Right now, deciding when and where to open new restaurants is largely a subjective process based on the personal judgement and experience of development teams. This subjective data is difficult to accurately extrapolate across geographies and cultures.
New restaurant sites take large investments of time and capital to get up and running. When the wrong location for a restaurant brand is chosen, the site closes within 18 months and operating losses are incurred.
Finding a mathematical model to increase the effectiveness of investments in new restaurant sites would allow TFI to invest more in other important business areas, like sustainability, innovation, and training for new employees. Using demographic, real estate, and commercial data, this competition challenges you to predict the annual restaurant sales of 100,000 regional locations.
Huge Dataset
Real time Problem
-Gives domain knowledge as well
Mall Customer Segmentation Data - Clustering Problem
Market Basket Analysis Kaggle : https://www.kaggle.com/vjchoudhary7/customer-segmentation-tutorial-in-python Problem Statement: You are owing a supermarket mall and through membership cards , you have some basic data about your customers like Customer ID, age, gender, annual income and spending score.
Spending Score is something you assign to the customer based on your defined parameters like customer behavior and purchasing data.
Unsupervised Learning
Market Basket Analysis
How to achieve customer segmentation using machine learning algorithm (KMeans Clustering) in Python
Who are your target customers with whom you can start marketing strategy [easy to converse]
How the marketing strategy works in real world
Converting Unsupervised to Supervised Learning
Chronic Kidney Disease - Classification Problem
Data has 25 features which may predict a patient with chronic kidney disease Kaggle : https://www.kaggle.com/colearninglounge/chronic-kidney-disease Problem Statement: The data was taken over a 2-month period in India with 25 features ( eg, red blood cell count, white blood cell count, etc). The target is the 'classification', which is either 'ckd' or 'notckd' - ckd=chronic kidney disease. Use machine learning techniques to predict if a patient is suffering from a chronic kidney disease or not.
netali514
commented
3 years ago
Restaurant Revenue Prediction - Regression problem
Predict annual restaurant sales based on objective measurements
Kaggle : https://www.kaggle.com/c/restaurant-revenue-prediction
Problem Statement: With over 1,200 quick service restaurants across the globe, TFI is the company behind some of the world's most well-known brands: Burger King, Sbarro, Popeyes, Usta Donerci, and Arby’s. They employ over 20,000 people in Europe and Asia and make significant daily investments in developing new restaurant sites.
Right now, deciding when and where to open new restaurants is largely a subjective process based on the personal judgement and experience of development teams. This subjective data is difficult to accurately extrapolate across geographies and cultures.
New restaurant sites take large investments of time and capital to get up and running. When the wrong location for a restaurant brand is chosen, the site closes within 18 months and operating losses are incurred.
Finding a mathematical model to increase the effectiveness of investments in new restaurant sites would allow TFI to invest more in other important business areas, like sustainability, innovation, and training for new employees. Using demographic, real estate, and commercial data, this competition challenges you to predict the annual restaurant sales of 100,000 regional locations.
Mall Customer Segmentation Data - Clustering Problem
Market Basket Analysis
Kaggle : https://www.kaggle.com/vjchoudhary7/customer-segmentation-tutorial-in-python
Problem Statement: You are owing a supermarket mall and through membership cards , you have some basic data about your customers like Customer ID, age, gender, annual income and spending score. Spending Score is something you assign to the customer based on your defined parameters like customer behavior and purchasing data.
Chronic Kidney Disease - Classification Problem
Data has 25 features which may predict a patient with chronic kidney disease
Kaggle : https://www.kaggle.com/colearninglounge/chronic-kidney-disease
Problem Statement: The data was taken over a 2-month period in India with 25 features ( eg, red blood cell count, white blood cell count, etc). The target is the 'classification', which is either 'ckd' or 'notckd' - ckd=chronic kidney disease. Use machine learning techniques to predict if a patient is suffering from a chronic kidney disease or not.