通过构建自定义 AI 模型来学习“抱脸”
上次更新时间：2024-11-24
课程售价: 2.9 元
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课程内容
- 01. Introduction (Hugging Face Ecosystem and Text Classification) - Zero - 1920x1080 619K (免费)
- 02. More Text Classification Examples - Zero - 1920x1080 490K (免费)
- 03. What We're Going To Build! - Zero - 1920x1080 810K
- 04. Getting Setup Adding Hugging Face Tokens to Google Colab - Zero - 1920x1080 868K
- 05. Getting Setup Importing Necessary Libraries to Google Colab - Zero - 1920x1080 914K
- 06. Downloading a Text Classification Dataset from Hugging Face Datasets - Zero - 1920x1080 818K
- 07. Preparing Text Data for Use with a Model - Part 1 Turning Our Labels into Numbers - Zero - 1920x1080 661K
- 08. Preparing Text Data for Use with a Model - Part 2 Creating Train and Test Sets - Zero - 1920x1080 582K
- 09. Preparing Text Data for Use with a Model - Part 3 Getting a Tokenizer - Zero - 1920x1080 892K
- 10. Preparing Text Data for Use with a Model - Part 4 Exploring Our Tokenizer - Zero - 1920x1080 700K
- 11. Preparing Text Data for Use with a Model - Part 5 Creating a Function to Tokenize Our Data - Zero - 1920x1080 883K
- 12. Setting Up an Evaluation Metric (to measure how well our model performs) - Zero - 1920x1080 788K
- 13. Introduction to Transfer Learning (a powerful technique to get good results quickly) - Zero - 1920x1080 780K
- 14. Model Training - Part 1 Setting Up a Pretrained Model from the Hugging Face Hub - Zero - 1920x1080 1022K
- 15. Model Training - Part 2 Counting the Parameters in Our Model - Zero - 1920x1080 903K
- 16. Model Training - Part 3 Creating a Folder to Save Our Model - Zero - 1920x1080 856K
- 17. Model Training - Part 4 Setting Up Our Training Arguments with TrainingArguments - Zero - 1920x1080 1233K
- 18. Model Training - Part 5 Setting Up an Instance of Trainer with Hugging Face Transformers - Zero - 1920x1080 1119K
- 19. Model Training - Part 6 Training Our Model and Fixing Errors Along the Way - Zero - 1920x1080 933K
- 20. Model Training - Part 7 Inspecting Our Models Loss Curves - Zero - 1920x1080 807K
- 21. Model Training - Part 8 Uploading Our Model to the Hugging Face Hub - Zero - 1920x1080 1009K
- 22. Making Predictions on the Test Data with Our Trained Model - Zero - 1920x1080 865K
- 23. Turning Our Predictions into Prediction Probabilities with PyTorch - Zero - 1920x1080 839K
- 24. Sorting Our Model's Predictions by Their Probability - Zero - 1920x1080 651K
- 25. Performing Inference - Part 1 Discussing Our Options - Zero - 1920x1080 807K
- 26. Performing Inference - Part 2 Using a Transformers Pipeline (one sample at a time) - Zero - 1920x1080 890K
- 27. Performing Inference - Part 3 Using a Transformers Pipeline on Multiple Samples at a Time (Batching) - Zero - 1920x1080 1160K
- 28. Performing Inference - Part 4 Running Speed Tests to Compare One at a Time vs. Batched Predictions - Zero - 1920x1080 826K
- 29. Performing Inference - Part 5 Performing Inference with PyTorch - Zero - 1920x1080 851K
- 30. OPTIONAL - Putting It All Together from Data Loading, to Model Training, to making Predictions on Custom Data - Zero - 1920x1080 848K
- 31. Turning Our Model into a Demo - Part 1 Gradio Overview - Zero - 1920x1080 997K
- 32. Turning Our Model into a Demo - Part 2 Building a Function to Map Inputs to Outputs - Zero - 1920x1080 684K
- 33. Turning Our Model into a Demo - Part 3 Getting Our Gradio Demo Running Locally - Zero - 1920x1080 777K
- 34. Making Our Demo Publicly Accessible - Part 1 Introduction to Hugging Face Spaces and Creating a Demos Directory - Zero - 1920x1080 650K
- 35. Making Our Demo Publicly Accessible - Part 2 Creating an App File - Zero - 1920x1080 980K
- 36. Making Our Demo Publicly Accessible - Part 3 Creating a README File - Zero - 1920x1080 820K
- 37. Making Our Demo Publicly Accessible - Part 4 Making a Requirements File - Zero - 1920x1080 872K
- 38. Making Our Demo Publicly Accessible - Part 5 Uploading Our Demo to Hugging Face Spaces and Making it Publicly Available - Zero - 1920x1080 940K
- 39. Summary Exercises and Extensions - Zero - 1920x1080 1213K
课程内容
39个讲座
- 01. Introduction (Hugging Face Ecosystem and Text Classification) - Zero - 1920x1080 619K (免费)
- 02. More Text Classification Examples - Zero - 1920x1080 490K (免费)
- 03. What We're Going To Build! - Zero - 1920x1080 810K
- 04. Getting Setup Adding Hugging Face Tokens to Google Colab - Zero - 1920x1080 868K
- 05. Getting Setup Importing Necessary Libraries to Google Colab - Zero - 1920x1080 914K
- 06. Downloading a Text Classification Dataset from Hugging Face Datasets - Zero - 1920x1080 818K
- 07. Preparing Text Data for Use with a Model - Part 1 Turning Our Labels into Numbers - Zero - 1920x1080 661K
- 08. Preparing Text Data for Use with a Model - Part 2 Creating Train and Test Sets - Zero - 1920x1080 582K
- 09. Preparing Text Data for Use with a Model - Part 3 Getting a Tokenizer - Zero - 1920x1080 892K
- 10. Preparing Text Data for Use with a Model - Part 4 Exploring Our Tokenizer - Zero - 1920x1080 700K
- 11. Preparing Text Data for Use with a Model - Part 5 Creating a Function to Tokenize Our Data - Zero - 1920x1080 883K
- 12. Setting Up an Evaluation Metric (to measure how well our model performs) - Zero - 1920x1080 788K
- 13. Introduction to Transfer Learning (a powerful technique to get good results quickly) - Zero - 1920x1080 780K
- 14. Model Training - Part 1 Setting Up a Pretrained Model from the Hugging Face Hub - Zero - 1920x1080 1022K
- 15. Model Training - Part 2 Counting the Parameters in Our Model - Zero - 1920x1080 903K
- 16. Model Training - Part 3 Creating a Folder to Save Our Model - Zero - 1920x1080 856K
- 17. Model Training - Part 4 Setting Up Our Training Arguments with TrainingArguments - Zero - 1920x1080 1233K
- 18. Model Training - Part 5 Setting Up an Instance of Trainer with Hugging Face Transformers - Zero - 1920x1080 1119K
- 19. Model Training - Part 6 Training Our Model and Fixing Errors Along the Way - Zero - 1920x1080 933K
- 20. Model Training - Part 7 Inspecting Our Models Loss Curves - Zero - 1920x1080 807K
- 21. Model Training - Part 8 Uploading Our Model to the Hugging Face Hub - Zero - 1920x1080 1009K
- 22. Making Predictions on the Test Data with Our Trained Model - Zero - 1920x1080 865K
- 23. Turning Our Predictions into Prediction Probabilities with PyTorch - Zero - 1920x1080 839K
- 24. Sorting Our Model's Predictions by Their Probability - Zero - 1920x1080 651K
- 25. Performing Inference - Part 1 Discussing Our Options - Zero - 1920x1080 807K
- 26. Performing Inference - Part 2 Using a Transformers Pipeline (one sample at a time) - Zero - 1920x1080 890K
- 27. Performing Inference - Part 3 Using a Transformers Pipeline on Multiple Samples at a Time (Batching) - Zero - 1920x1080 1160K
- 28. Performing Inference - Part 4 Running Speed Tests to Compare One at a Time vs. Batched Predictions - Zero - 1920x1080 826K
- 29. Performing Inference - Part 5 Performing Inference with PyTorch - Zero - 1920x1080 851K
- 30. OPTIONAL - Putting It All Together from Data Loading, to Model Training, to making Predictions on Custom Data - Zero - 1920x1080 848K
- 31. Turning Our Model into a Demo - Part 1 Gradio Overview - Zero - 1920x1080 997K
- 32. Turning Our Model into a Demo - Part 2 Building a Function to Map Inputs to Outputs - Zero - 1920x1080 684K
- 33. Turning Our Model into a Demo - Part 3 Getting Our Gradio Demo Running Locally - Zero - 1920x1080 777K
- 34. Making Our Demo Publicly Accessible - Part 1 Introduction to Hugging Face Spaces and Creating a Demos Directory - Zero - 1920x1080 650K
- 35. Making Our Demo Publicly Accessible - Part 2 Creating an App File - Zero - 1920x1080 980K
- 36. Making Our Demo Publicly Accessible - Part 3 Creating a README File - Zero - 1920x1080 820K
- 37. Making Our Demo Publicly Accessible - Part 4 Making a Requirements File - Zero - 1920x1080 872K
- 38. Making Our Demo Publicly Accessible - Part 5 Uploading Our Demo to Hugging Face Spaces and Making it Publicly Available - Zero - 1920x1080 940K
- 39. Summary Exercises and Extensions - Zero - 1920x1080 1213K