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Mercari Price Suggestion Challenge Data Science Project

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

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What will you learn

  • Creating auto calculating pricing model
  • Use of different ML algorithms
  • Implementation using Python
  • Exploring product associations
  • Exploratory price calculations

What will you get

  • Access to recording of the complete project
  • Access to all material related to project like data files, solution files etc.

Prerequisites

  • Jupyter Notebook from Anaconda installation
  • At least 4 GB RAM MachineLanguage used: Python or R

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.

Instructors

 
Pradeepta

Curriculum For This Mini Project

 
  Problem Statement
00:01:15
  Import Data Sets
00:02:33
  Import Libraries
00:00:34
  Exploratory Data Analysis
00:04:45
  What is the Variation in Prices?
00:08:11
  How good is the condition of products?
00:10:49
  How good shipping condition is?
00:08:07
  What are the most expensive brands?
00:07:19
  Do Expensive brands have high prices?
00:00:26
  How many categories are there?
00:02:50
  Do prices vary by category?
00:12:08
  How do you predict the price?
00:06:33
  Does Item description impact price?
00:15:01
  Document Feature Matrix
00:07:23
  N-gram approach to extract features
00:19:16
  Creating new features
00:09:45
  Predict Prices
00:02:14
  Additional features
00:06:50
  Implementing in Python
00:07:48
  Q n A session
00:20:10