ABC Analysis with Machine Learning || Python

Welcome to our YouTube video on ABC Analysis with Machine Learning! In this tutorial, we will walk you through the process of sorting and categorizing sales data using machine learning techniques.

🔎 Understanding ABC Analysis:
ABC Analysis is a method used to classify items based on their importance and contribution to revenue. We'll explore how to categorize the elements of a dataset into A, B, and C categories, where A items generate the majority of income, B items generate a moderate amount, and C items contribute the least.

📊 Data Preparation:
To get started, we'll import the necessary packages and read a popular online retailer dataset, which includes clothing sales data throughout the summer. The dataset provides information on the number of units sold, price per item, and total revenue generated. We'll perform data preparation tasks such as calculating revenue and visualizing the distribution of sales.

🔧 Applying Machine Learning:
Next, we'll dive into the application of machine learning algorithms, specifically the K-Means Clustering algorithm, to train our model. By clustering the revenue distributions, we'll assign each item to the appropriate A, B, or C category. We'll explain the process step-by-step and showcase the results of the classification.

📈 Analyzing Results:
Once the model is trained and the categories are assigned, we'll analyze the final distribution of items. We'll reveal the percentage of articles and turnover associated with each category: A, B, and C. The insights gained from this analysis can help businesses make informed decisions and focus on high-impact items.

If you're interested in data analysis, machine learning, and optimizing business strategies, this video is for you! Don't forget to leave your questions and comments below. Subscribe to our channel for more insightful content on machine learning and stay updated with the latest trends in the industry.

🔗 Links:
Dataset Download: [Link to Dataset]
https://github.com/amankharwal/Website-data/blob/master/summer-products-with-rating-and-performance_2020-08.csv