Offered By: IBM

Find your Best Bottle of Wine with NLP

Imagine you come into a wine store, and a knowledgeable vintner tells you all that you want to know about their wines and helps you select the best bottle based on your tastes and cravings. Since you had such a good experience you may buy more wine. This may even give you an idea to open an online wine store, based on a recommender system that provides the same recommendations, as the knowledgeable vintner.

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GPXX0SV2EN

Machine Learning

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At a Glance

Imagine you come into a wine store, and a knowledgeable vintner tells you all that you want to know about their wines and helps you select the best bottle based on your tastes and cravings. Since you had such a good experience you may buy more wine. This may even give you an idea to open an online wine store, based on a recommender system that provides the same recommendations, as the knowledgeable vintner.

Imagine you come into a wine store, and a knowledgeable vintner tells you all that you want to know about their wines and helps you select the best bottle based on your tastes and cravings. Since you had such a good experience you may buy more wine. This may even give you an idea to open an online wine store, based on a recommender system that provides the same recommendations, as the knowledgeable vintner.

In this Guided Project, you will use wine dataset and perform some data wrangling techniques to extract interesting information about wines, as well as you will use some Natural Language Processing (NLP) tools to build a recommender system for selecting wines.

A Look at the Project Ahead

After completing this lab you will be able to:

- extract information from wine dataset
- use Hugging Face Transformer model to create embeddings
- create a search function and visual search explorer to select wines

What You'll Need

You just need a web browser! Basic Python programming knowledge is strongly recommended.
Everything else is provided to you via the IBM Skills Network Labs environment, where you will have access to the Cloud IDE and Python runtimes that we offer as part of the IBM Skills Network Labs environment. Remember that the IBM Skills Network Labs environment comes with many things pre-installed (e.g. Docker) to save them the hassle of setting everything up. Also note that this platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer or Safari.

Estimated Effort

30 min

Level

Intermediate

Industries

Retail

Skills You Will Learn

Python, Data Science, Machine Learning, Data Analysis, Embeddable AI

Language

English

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Instructors

Svitlana Kramar

Data Scientist

I’m a passionate data science educator whose goal is to learn by teaching innovative data science tools that can improve our day-to-day tasks and our quality of life. My interests are in Natural Language Processing: text classification, summarization, and generation. Research can take a long time because there are a lot of resources and new opinions posted every day. Having tools to summarize and extract the information can save a lot of time. I hope we can all learn, approve, and apply the data science tools to cut down on the repetitive and tedious tasks, to make more informed decisions in life, to differentiate fake from real, and to open communication spaces to language-diverse or hearing-impaired audiences. The applications are limitless! My personality: I am a foodie and I love cooking and learning different cuisines. I also love travelling and connecting with people by learning a little bit of their language, about their food and music. I hold Data Science and Analytics master’s degree, specializing in Machine Learning, from University of Calgary.

Contributors

Joseph Santarcangelo

Senior Data Scientist at IBM

Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.

Sheng-Kai Chen

Data Scientist

Sheng-Kai Chen is a graduate student at the University of Toronto, concentrating on Information Systems & Design. Having several experiences analyzing data for retail stores and designing small software for small businesses. Sheng-Kai was inspired to shift toward answering new challenges with machine learning and new technics.