5. Machine Learning for Retail (Janani Ravi, 2021)

1. Course Overview: 1. Course Overview 00:00:00 2. Exploring Applications of Machine Learning in Retail: 01. Version Check 00:02:10 02. Prerequisites and Course Outline 00:02:26 03. Digital Trends in Retail 00:04:03 04. Use Cases for ML in Retail - Predicting Customer Behavior 00:09:49 05. Use Cases for ML in Retail - Visual Search and Voice Search 00:14:45 06. Use Cases of ML in Retail - Virtual Assistants and Chatbots 00:18:21 07. Use Cases of ML in Retail - Price and Inventory Prediction 00:21:27 08. Use Cases of ML in Retail - Behavior Tracking via Video Analytics 00:26:46 09. Machine Learning for Visual Search 00:30:38 10. Challenges Applying Machine Learning in Retail 00:37:51 3. Case Study - Optimizing Product Prices Using Machine Learning: 1. Price Elasticity of Demand 00:43:19 2. Price Optimization - Background and Context 00:48:40 3. Price Optimization - Data Sources Feature Engineering and Models 00:52:58 4. Price Optimization - Price Elasticity Linear Programming and Results 00:58:36 4. Case Study - Optimizing Supply Planning Using Machine Learning: 1. AI in The Supply Chain and Route Optimization 01:04:35 2. Dynamic Vehicle Routing - Background and Context 01:09:06 3. Dynamic Vehicle Routing - Three Stage Workflow and Results 01:16:01 5. Applying Machine Learning Techniques to Retail Data: 01. Association Rules Learning 01:22:46 02. Frequent Itemsets and Support 01:25:39 03. Confidence Lift and Conviction 01:29:36 04. Apriori Algorithm 01:32:25 05. Demo - Data Cleaning and Preparation 01:34:13 06. Demo - Data Exploration 01:39:04 07. Demo - Transaction Encoding 01:43:41 08. Demo - Frequent Itemsets and Association Rules Using Support 01:47:11 09. Demo - Frequent Itemsets and Association Rules Using Confidence and Lift 01:51:27 10. Demo - Recommending Top 5 Products 01:55:01 11. Summary References and Further Study 01:58:19