Machine Learning for Sequential Data
In this project, we will analyze various sequential data types like text streams, audio clips, time-series data, and genetic data, and understand pre-processing techniques associated with each.
Language
- English
Topic
- Machine Learning
Enrollment Count
- 1.75K
Skills You Will Learn
- Python, Data Science, Machine Learning
Offered By
- IBM
Estimated Effort
- 45 minutes
Platform
- SkillsNetwork
Last Update
- December 21, 2024
Sequential modelling is the process of forecasting a sequence of values from a set of input values. Input values can contain elements that are ordered into sequences like time-series, text streams, or DNA sequences. Lot of tasks can be modelled from these types of data. For example:
- text classification, e.g. spam email or not
- language translation, e.g. French to English
- time-series forecasting, e.g. stock prices prediction
A Look at the Project Ahead
After completing this Guided Project, you will be able to:
- Describe various forms of sequential data, and common tasks that can be modelled using sequential data
- Decompose a time-series and perform time-series imputation
- Pre-process and vectorize a text stream and genetic dataset
- Pre-process and visualize an audio dataset, and create spectrograms
This course mainly uses Python and JupyterLabs. Although these skills are recommended prerequisites, no prior experience is required as this Guided Project is designed for complete beginners.
Frequently Asked Questions
Your Instructor
Kopal Garg
I am a Data Scientist Intern at IBM, and a Masters student in computer science at the University of Toronto. I am passionate about building AI-based solutions that improve various aspects of human life.
Language
- English
Topic
- Machine Learning
Enrollment Count
- 1.75K
Skills You Will Learn
- Python, Data Science, Machine Learning
Offered By
- IBM
Estimated Effort
- 45 minutes
Platform
- SkillsNetwork
Last Update
- December 21, 2024
Instructors
Kopal Garg
Data Scientist Intern at IBM
I am a Data Scientist Intern at IBM, and a Masters student in Computer Science at the University of Toronto. I am passionate about building data science, and machine learning-based systems for improving various aspects of life.
Read moreContributors
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.
Read moreCindy Huang
Data Science Intern at IBM
Hey there! I'm a senior at the University of Toronto studying data science. My passion for machine learning lies in NLP and using technology to improve human experience.
Read more