Deep Learning Literacy - Practical Application
- 12 courses
- 9 hours
Deep learning is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised.
This path is focused on Deep Learning in action. We have pulled a series of examples to demonstrate how deep learning is embedded in our day to day lives. These are just in time sort of courses that reflect the journey from problem to solution.
The path is curated for Data enthusiasts that are eager to learn about Deep learning and foray into Data centered roles like Data scientist. Though this path will contain workable solutions, there is no requirement for the learner to have any background into Machine Learning or Deep learning. Intention is to have sandboxes for the path.
Courses in this path
This path is designed to explore the application of Deep Learning in our day to day lives. This section focuses on a few industry examples of Deep Learning Practical applications.
This section of the path focuses on RNN, CNN and GAN’s implementation and exploring how deep learning solves problems like automating image captioning and sentiment classification.
This section explores practical examples of word embedding, Sentence classification, Named Entity Recognition and Recommendation Engines.