This course is designed for anyone interested in working on unstructured data such as text and images to perform classification, clustering, visualizations.

Must have taken course: Artificial Intelligence and Machine Learning Basics for Non-Programmers

Course Outline:

1. Introduction to Deep Learning

• Understanding the basics of artificial intelligence and machine learning
• Predictive and Generative Models
• Overview of neural networks and deep learning concepts
• Applications of deep learning in text, image, and time series data
• Demo: Using neural networks

2. Working with images

• Introduction to image data and image representation
• Leveraging knowledge learnt by community to handle images (transfer learning)
• Using Orange’s deep learning toolbox for image classification
• Hands-on: Building multiple models to perform binary and multi-class classification of images

3. Working with Text

• Introduction to text data and its different uses in deep learning
• Preprocessing text data for deep learning tasks
• Understanding word embeddings and text representations in Orange
• Hands-on: Learn how to build model to perform sentiment analysis on movie review data using couple of word embedding techniques

4. Handling Time Series data

• Understanding time series data and its unique characteristics
• Leveraging different prebuild models in Orange to perform time series forecasting
• Hands-on: Build model to forecast Google stock price based on historical data

5. Visualizing Geo Data

• Understanding what Geo location data
• Using Orange to quickly visualize data based on Geo location
• Hands-on: Use Orange to visualize data based on Latitude and Longitude

Training material provided: Yes (Digital format)

Hands-on Lab: Students must install Orange Data Mining software.