Mercari Price Suggestion Challenge Data Science Project

Data Science Project in Python- Build a machine learning algorithm that automatically suggests the right product prices.


Each project comes with 2-5 hours of micro-videos explaining the solution.

Code & Dataset

Get access to 50+ solved projects with iPython notebooks and datasets.

Project Experience

Add project experience to your Linkedin/Github profiles.

What will you learn

  • Understanding the problem statement

  • Importing the dataset from AWS

  • Importing important libraries and understanding its significance

  • Understanding CSR Matrix and hstack

  • Performing basic EDA and checking for null values

  • Creating function for handling null values

  • Performing slicing and making function for converting variables into categorical types

  • Merging two or more Dataset

  • Using TFIDF and Count Vectorizer for analyzing textual data

  • Applying LabelBinarizer for textual data

  • Sparse matrix its use and implementation

  • Selecting models Light GBM and Ridge as model

  • Defining parameters for the models

  • Training the model and using the model for making predictions

  • Saving the final predictions in CSV format

Project Description

Mercari, Japan’s biggest community-powered shopping app, knows this problem deeply. They’d like to offer pricing suggestions to sellers, but this is tough because their sellers are enabled to put just about anything, or any bundle of things, on Mercari's marketplace.

In this machine learning project, we will build an algorithm that automatically suggests the right product prices. You’ll be provided user-inputted text descriptions of their products, including details like product category name, brand name, and item condition.

Similar Projects

Big Data Project Job Recommendation Challenge-Predict which jobs users will apply
Build a machine learning model that will predict which jobs users will apply to given their past applications, demographics and work history.
Big Data Project Home Depot Product Search Relevance ML Project in Python
Given a customer's search query and the returned product in text format, your predictive model needs to tell whether it is what the customer was looking for.
Big Data Project Learn to prepare data for your next machine learning project
Text data requires special preparation before you can start using it for any machine learning project.In this ML project, you will learn about applying Machine Learning models to create classifiers and learn how to make sense of textual data.
Big Data Project Predicting interest level of Rental Listings on RentHop
In this data science project, we will predict the number of inquiries a new listing receives based on the listing's creation date and other features.

Curriculum For This Mini Project

  Problem Statement
  Import Data Sets
  Import Libraries
  Exploratory Data Analysis
  What is the Variation in Prices?
  How good is the condition of products?
  How good shipping condition is?
  What are the most expensive brands?
  Do Expensive brands have high prices?
  How many categories are there?
  Do prices vary by category?
  How do you predict the price?
  Does Item description impact price?
  Document Feature Matrix
  N-gram approach to extract features
  Creating new features
  Predict Prices
  Additional features
  Implementing in Python
  Q n A session