Apparel Recommendation Engine Workshop
Python for Data Science: Data Structures
Python for Data Science: Functions
Python for Data Science: NUMPY
Python for Data Science: Pandas
Data acquisition and understanding
Data cleaning and understanding
Basics of Linear Algebra
Text based product similarity
Text Semantics based product similarity
Deep learning based visual product similarity
How do we measure the goodness of our solutions?
Personalized product recommendations are the alternative way of navigating through the online shop. More people find products they need. Even if they didn’t think of them.
Build a recommendation engine which suggests similar products to the given product in any e-commerce websites ex. Amazon.com, myntra.com etc
Objective of AI Work shop:
- To give a flavour of what is Machine Learning/Artificial Intelligence
- To introduce you how a real world machine learning problem can be solved
In this work shop we will build a recommendation engine that suggests relevant apparels to the given apparel
The recommendation engine, uses information about 1,80,000 products and each product will have multiple features named
- Title of the product
- Brand of the product
- Color of the product
- Type of the product
- Image of the apparel
Data Source: Amazon.com
- Validity of this workshop is 100 days( i.e Starts from the date of your registration to this course)
- No prerequisites– we will teach every thing from basics ( we just expect you to know basic programming)
- Python for Data science is part of this curriculum.
We are building our workshop content and teaching methodology to cater to the needs to students at various levels of expertise and varying background skills. This workshop can be taken by anyone with a working knowledge of a modern programming language like C/C++/Java/Python. We expect the average student to spend at least 15 hours. More the effort, better the results. Here is a list of customers who would benefit from our workshop:
- Undergrad (BS/BTech/BE) students in engineering and science.
- Grad(MS/MTech/ME/MCA) students in engineering and science.
- Working professionals: Software engineers, Business analysts, Product managers, Program managers, Managers, Startup teams building ML products/services.
- Lectures 54
- Quizzes 0
- Duration 10 hours
- Skill level All levels
- Language English
- Students 4956
- Assessments Yes