From 53423cf85180e805f3f7a3f1238822ed3d15b7a1 Mon Sep 17 00:00:00 2001 From: Daniel Bourke Date: Sat, 16 Apr 2022 13:42:09 +1000 Subject: [PATCH] update log --- README.md | 13 ++++++++----- 1 file changed, 8 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 846ca13e..dba098d1 100644 --- a/README.md +++ b/README.md @@ -20,12 +20,13 @@ Launch early 2022. | [00 - PyTorch Fundamentals](https://www.learnpytorch.io/00_pytorch_fundamentals/) | Many fundamental PyTorch operations used for deep learning and neural networks. | [Go to exercises & extra-curriculum](https://www.learnpytorch.io/00_pytorch_fundamentals/#exercises) | [Go to slides](https://github.com/mrdbourke/pytorch-deep-learning/blob/main/slides/00_pytorch_and_deep_learning_fundamentals.pdf) | | [01 - PyTorch Workflow](https://www.learnpytorch.io/01_pytorch_workflow/) | Provides an outline for approaching deep learning problems and building neural networks with PyTorch. | [Go to exercises & extra-curriculum](https://www.learnpytorch.io/01_pytorch_workflow/#exercises) | [Go to slides](https://github.com/mrdbourke/pytorch-deep-learning/blob/main/slides/01_pytorch_workflow.pdf) | | [02 - PyTorch Neural Network Classification](https://www.learnpytorch.io/02_pytorch_classification/) | Uses the PyTorch workflow from 01 to go through a neural network classification problem. | [Go to exercises & extra-curriculum](https://www.learnpytorch.io/02_pytorch_classification/#exercises) | [Go to slides](https://github.com/mrdbourke/pytorch-deep-learning/blob/main/slides/02_pytorch_classification.pdf) | -| [03 - PyTorch Computer Vision](https://www.learnpytorch.io/03_pytorch_computer_vision/) | Let's see how PyTorch can be used for computer vision problems using the same workflow from 01 & 02. | Go to exercises & extra-curriculum | Go to slides | -| Coming soon: 04 - PyTorch Custom Datasets | How do you load a custom dataset into PyTorch? Also we'll be laying the foundations in this notebook for our modular code (covered in 05). | Go to exercises & extra-curriculum | Go to slides | +| [03 - PyTorch Computer Vision](https://www.learnpytorch.io/03_pytorch_computer_vision/) | Let's see how PyTorch can be used for computer vision problems using the same workflow from 01 & 02. | [Go to exercises & extra-curriculum](https://www.learnpytorch.io/03_pytorch_computer_vision/#exercises) | Go to slides | +| [04 - PyTorch Custom Datasets](https://www.learnpytorch.io/04_pytorch_custom_datasets/) | How do you load a custom dataset into PyTorch? Also we'll be laying the foundations in this notebook for our modular code (covered in 05). | Go to exercises & extra-curriculum | Go to slides | | Coming soon: 05 - Going modular | PyTorch is designed to be modular, let's turn what we've created into a series of Python scripts (this is how you'll often find PyTorch code in the wild). | Go to exercises & extra-curriculum | Go to slides | | Coming soon: 06 - PyTorch Transfer Learning | Let's take a well performing pre-trained model and adjust it to one of our own problems. | Go to exercises & extra-curriculum | Go to slides | | Coming soon: 07 - Milestone Project 1: PyTorch Experiment Tracking | We've built a bunch of models... wouldn't it be good to track how they're all going? | Go to exercises & extra-curriculum | Go to slides | | Coming soon: 08 - Milestone Project 2: PyTorch Paper Replicating | PyTorch is the most popular deep learning framework for machine learning research, let's see why by replicating a machine learning paper. | Go to exercises & extra-curriculum | Go to slides | +| Coming soon: 09 - Milestone Project 3: Model deployment | So you've built a working PyTorch model... how do you get it in the hands of others? Hint: deploy it to the internet. | Go to exercises & extra-curriculum | Go to slides | ### Old outline version (will update this if necessary) @@ -50,19 +51,20 @@ code/ 6. PyTorch transfer learning - Let's improve upon the models we've built ourselves using transfer learning. 7. PyTorch experiment tracking - We've built a bunch of models... wouldn't it be good to track how they're all going? 8. PyTorch paper replicating - Let's see why PyTorch is the most popular deep learning framework for machine learning research by replicating a machine learning research paper with it. +9. PyTorch model deployment - How do you get your PyTorch models in the hands of others? Each notebook will teach a maximum of 3 big ideas. ## Status -* **Working on:** exercises and solutions for notebook 03, 04 +* **Working on:** exercises and solutions for notebook 04 * **Total video count:** 90 -* **Next:** annotate notebooks 03, 04, 05 with text then make slides and images +* **Next:** finish exericses/solutions for 04, then record videos for 03, 04 * **Done skeleton code for:** 00, 01, 02, 03, 04, 05, 06, 07 * **Done annotations (text) for:** 00, 01, 02, 03, 04 * **Done images for:** 00, 01, 02, 03, 04 * **Done keynotes for:** 00, 01, 02, 03 -* **Done exercises and solutions for:** 00, 01, 02 +* **Done exercises and solutions for:** 00, 01, 02, 03 * **Done vidoes for:** 00, 01, 02 ## TODO @@ -81,6 +83,7 @@ High-level overview of things to do: Almost daily updates of what's happening. +* 16 Apr 2022 - finish exercises/solutions for 03, added live-coding walkthrough of 03 exercises/soltuons YouTube: https://youtu.be/_PibmqpEyhA * 14 Apr 2022 - add final images/annotations for 04, begin on exercises/solutions for 03 & 04 * 13 Apr 2022 - add more images/annotations for 04 * 3 Apr 2022 - add more annotations for 04