elizabeth-ngandu/Carrefour-Kenya-Analysis

# Carrefour-Kenya-Analysis # Business Understanding You are a Data analyst at Carrefour Kenya and are currently undertaking a project that will inform the marketing department on the most relevant marketing strategies that will result in the highest no. of sales (total price including tax). Your project has been divided into four parts where you'll explore a recent marketing dataset by performing various unsupervised learning techniques and later providing recommendations based on your insights. # Specifying the question ### Part 1: Dimensionality Reduction This section of the project entails reducing your dataset to a low dimensional dataset using the t-SNE algorithm or PCA. You will be required to perform your analysis and provide insights gained from your analysis. Dataset: [Link (Links to an external site.)] ### Part 2: Feature Selection This section requires you to perform feature selection through the use of the unsupervised learning methods learned earlier this week. You will be required to perform your analysis and provide insights on the features that contribute the most information to the dataset. Dataset: [Link (Links to an external site.)] ### Part 3: Association Rules This section will require that you create association rules that will allow you to identify relationships between variables in the dataset. You are provided with a separate dataset that comprises groups of items that will be associated with others. Just like in the other sections, you will also be required to provide insights for your analysis. Dataset: [Link (Links to an external site.)] ### Part 4: Anomaly Detection You have also been requested to check whether there are any anomalies in the given sales dataset. The objective of this task being fraud detection. Dataset: [Link (Links to an external site.)] # Metrics for success Dataset with reduced dimensions Get the features that contribute the most information Provide association rules for the store Check for fraud det …