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- AI
- Data
Deep Learning Literacy - Practical Application
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.
Content in this path
Beginner
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.
Intermediate
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.
Advanced
This section explores practical examples of word embedding, Sentence classification, Named Entity Recognition and Recommendation Engines.
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What You'll Learn
- Implement Image recognition with Convolutional Neural Network
- Implement Text Auto Completion with LSTM
- Implement Image Captioning with Recurrent Neural Networks
- Implement Natural Language Processing for Word Embedding
- Implement Sentence Classification with BERT
- Implement Named Entity Recognition with BERT
- Sentiment Classification with Recurrent Neural Networks
- Build a Rating Recommendation Engine with Collaborative Filtering
- Build an Object Detection Model with Python
- Build a model for Anomaly Detection in Time Series Data
- Implement Text to Image Translation with Generative adversarial Networks
- Deep Learning Application for Healthcare
- Deep Learning Application for Marketing
- Deep Learning Application for Finance
- Deep Learning Application for Retail
- Understanding of algorithms used in the path. Though it is desired but not mandatory
- Understanding of Deep Learning Key concepts
- Deep Learning an AI
- Deep Learning with Python
- Machine Learning Literacy
- Applied Machine Learnin
- Deep Learning Literacy
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