Objectives
- Deep learning (DL) models- DL optimisation techniques
- The overfitting problem and how to solve it
- Structure of Convolutional Neural Networks (CNN)
- Structure of Recurrent Neural Networks (RNN)
- CNN’s top architectures
- Basic natural language processing techniques
Lessons
About this course
About this Course:
This course is a specialised version of our Data Science I (Python), designed specifically for the National Data Science Challenge, organized by Shopee. In this course, students will learn advanced Deep Learning and Natural Language Processing techniques to prepare themselves for the advanced category of this challenge: Product Information Extraction
By the end of the course, students will be able to build advanced Deep Learning structures, namely a "classification" or "prediction" engines for product information extraction. Students will also learn to build Deep Learning models with an aim towards product information extraction. All coding and projects will be done in class, under the supervision of the instructor.
Whether you are thinking of registering or have registered for the National Data Science Challenge, joining this course will definitely give you the head start you need.
Prerequisites
This course requires a basic understanding of Python. You should either have sat and completed our Python Development Course or already have intermediate-level understanding of Python.
If you have not sat our Python Development course, a Student Affairs Officer will reach out to you upon registration to confirm your mastery of Python.