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Mastering NLP and Clustering: Find Best Courses Like a Pro

IntermediateGuided Project

In this project, you'll dive into the exciting realm of Natural Language Processing (NLP) and Machine Learning (ML) to identify similar courses. From preprocessing text to vectorizing it with cutting-edge NLP models like BERT, you'll master the art of preparing text for analysis. Get hands-on experience with clustering algorithms and find out the optimal number of clusters using various methods. Discover the beauty of data visualization as you plot similar courses in 2D and 3D. Finally, search and recommend clusters tailored to your specific interests - all in one project!

4.9 (17 Reviews)

Language

  • English

Topic

  • Data Science

Industries

  • Information Technology

Enrollment Count

  • 179

Skills You Will Learn

  • Python, Data Analysis, Machine Learning, Clustering, Recommendation

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 1 hour

Platform

  • SkillsNetwork

Last Update

  • May 1, 2024
About This Guided Project

A Look at the Project Ahead

Unlock the world of limitless learning possibilities! In this project, you will learn the essential skills of Natural Language Processing (NLP) and Machine Learning (ML) to identify similar courses like never before. You will start by preparing text for analysis through various stages, including cleaning, tokenization, and stemming. Then, you will use state-of-the-art NLP models like the BERT model to vectorize text for ML tasks. After that, you will learn how to determine the optimal number of clusters using different methods such as the elbow method, silhouette score, and gap statistic. You will then use the K-means algorithm for clustering and visualize similar courses in 2D and 3D plots. The project will culminate in searching and recommending the cluster based on your search term. This project is a perfect opportunity to gain hands-on experience in NLP and ML while also learning how to apply these techniques to real-world problems.   

In this project, you will learn how to:
  1. Prepare text for analysis through various stages
  2. Vectorize text for ML tasks using state-of-the-art NLP models (the BERT model for embeddings)
  3. Determine the optimal number of clusters using different methods
  4. Use the K-means algorithm for clustering
  5. Visualize similar courses in 2D and 3D plots
  6. Search and recommend the cluster based on your search term

What You'll Need

A browser, and little background in python, and how to use Jupyter Notebook.

Instructors

Sina Nazeri

Data Scientist at IBM

I am grateful to have had the opportunity to work as a Research Associate, Ph.D., and IBM Data Scientist. Through my work, I have gained experience in unraveling complex data structures to extract insights and provide valuable guidance.

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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.

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Contributors

Rohit Arora

Full-Stack Software Engineer

A lifelong learner who develops cool technology. Join me to gain knowledge about the breadth of software development 😎.

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Roxanne Li

Data Scientist at IBM

I am an aspiring Data Scientist at IBM with extensive theoretical/academic, research, and work experience in different areas of Machine Learning, including Classification, Clustering, Computer Vision, NLP, and Generative AI. I've exploited Machine Learning to build data products for the P&C insurance industry in the past. I also recently became an instructor of the Unsupervised Machine Learning course by IBM on Coursera!

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J.C.(Junxing) Chen

Data scientist at IBM

Data science is easy and helpful! I want to let everyone know data science and help everyone using it for everyday life! Not only being a Data science guide person but also making friends, I want to make friends with peoples like you! As a data scienist, I hope my spread data science could help my friend!

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Jigisha Barbhaya

Data Scientist

I am a Data scientist at IBM and Lead instructor at Skills network. I love to learn and educate. I have completed my MSc(Computer Application) specialisation in Data science from Symbiosis University.

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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.

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Artem Arutyunov

Data Scientist

Hey, Artem here! I am excited about answering new challenges with data science, machine learning and especially Reinforcement Learning. Love helping people to learn, and learn myself. Studying Math and Stats at University of Toronto, hit me up if you are from there as well.

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