Offered By: IBM
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.
Continue readingGuided Project
Machine Learning
1.17k+ Enrolled5.0
At a Glance
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.
About
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:
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 notÂ
- language translation, e.g. French to English
- time-series forecasting, e.g. stock prices prediction
In this guided project, we will look into various common sequential data sets, and understand pre-processing techniques associated with each. Since we will be using simple methods, no prior knowledge in machine learning will be required to complete this guided project.Â
Â
 A Look at the Project Ahead
After completing this Guided Project, you will be able to:
 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 datasetÂ
- Pre-process and visualize an audio dataset, and create spectrograms
What You'll Need
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.
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
> Do I need to install any software to participate in this project?
Everything you need to complete this project will be provided to you via the Skills Network Labs and it will all be available via a standard web browser.
> What web browser should I use?
The Skills Network Labs platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer, or Safari.
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.Â
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.Â
Â