—————- General Concepts —————-
0:00  | Introduction 
0:40  | GPT-3/Codex/DALL·E
1:30  | Roadmap of video
2:35  | Creating the Azure OpenAI resource in your Azure portal
3:55  | Azure OpenAI Studio
3:56  | Features overview & application examples: summarization, classifying text, natural language to SQL, Generating new product names
7:58  | GPT-3 Playground overview
8:45  | Model deployments & how to create
9:05  | Models & considerations 
9:23  | Model naming convention
9:59  | Overview of GPT-3 models and capabilities: Davinci, Babbage, Ada, Curie
11:35| Overview of Codex models and capabilities: Cushman & Davinci
12:05| Recommendation for initial model deployment

——————- Customizing Models ——————-
13:05| Generating python snippet from the GPT-3 playground
14:00| Defining the parameters to tune: Temperature, Max length tokens, top probabilities, frequency penalty, presence penalty, best of, pre-response text, post-response text
19:25| Scenarios on how to adjust model parameters 
19:31| Scenario 1: low temperature, high top probability
21:06| Scenario 2: high temperature, high top probability, low frequency penalty
22:35| Scenario 3: moderate temperature, moderate top probability, low presence penalty

—————- Fine-tuning using the OpenAI API in Python —————-
24:15| Fine-tuning and use case, why would you want to fine-tune the model
24:42| Considerations: model size and its impact on computation and cost
25:20| Prompts and completions 
25:50| Generating prompts and completions using the MediaWiki API to generate random titles and responses for those titles in Wikipedia
26:33| Importing necessary libraries
27:08| creating 100 random responses and writing a function to get their summaries, training data format
32:35| Training and validating datasets in JSON lines & exporting datasets to file management in Azure OpenAI 
34:00| Creating customized model to fine-tine existing base models
35:30| Summary

———- Documentation ————
https://learn.microsoft.com/en-us/rest/api/cognitiveservices/azureopenaistable/fine-tunes/create?tabs=HTTP
https://learn.microsoft.com/en-us/azure/cognitive-services/openai/how-to/fine-tuning?pivots=programming-language-python
https://learn.microsoft.com/en-us/azure/cognitive-services/openai/concepts/models

source