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
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