Mastering NLP and Clustering: Find Best Courses Like a Pro
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
A Look at the Project Ahead
In this project, you will learn how to:
- Prepare text for analysis through various stages
- Vectorize text for ML tasks using state-of-the-art NLP models (the BERT model for embeddings)
- Determine the optimal number of clusters using different methods
- Use the K-means algorithm for clustering
- Visualize similar courses in 2D and 3D plots
- Search and recommend the cluster based on your search term
What You'll Need
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
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.
Read moreJoseph 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.
Read moreContributors
Rohit Arora
Full-Stack Software Engineer
A lifelong learner who develops cool technology. Join me to gain knowledge about the breadth of software development 😎.
Read moreRoxanne 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!
Read moreJ.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!
Read moreJigisha 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.
Read moreSheng-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.
Read moreArtem 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.
Read more