Week #1: A Fresh Start

1. New course units

With the start of the new challenge, two new course units come along and, with them, a fresh start as well.

For this challenge, the course units that will accompany it will be Machine Learning I and Planning and Decision Making.

The former, as the name suggests, will cover various topics about Machine Learning, all the way from problem definition and data preprocessing to ML algorithms and their evaluation/optimization.

On the other hand, the latter will cover several aspects about Planning and Decision Making, all the way from automatic problem solving and optimization techniques, such as search and evolutionary algorithms.

With these two course units in mind, it is worth noting that the theme chosen by the team for the challenge should allow the exploration of both subjects (e.g. an optimization problem that resorts to a machine learning technique to solve it, with the latter’s hyper parameters also being optimized by a genetic algorithm).

2. Ideas for the next challenge

Regarding ideas for this challenge, as stated before, the team is constrained to a problem that covers both course units’ subjects.

Luckily, in retail, there’s a very natural goal that all companies are looking into optimizing in any way possible: Sales and Profit.

As such, many are the strategies possible to work towards this goal:

• Product Pricing;

• Store Layout and Shelf Planning;

• Supply/Demand Analysis and Planning;

• Among others.

Given that companies have the necessary historical data, machine learning techniques can be applied to give them more insights on these topics (e.g. understand which products are commonly sold together) and automatically learn how to apply the aforementioned strategies to solve new scenarios.

Next week, the team should discuss these insights with the professors, in order to obtain feedback and help the team settle on the the theme for this challenge.