For getting started with a blog, I recommend FastPages.
- DataBlocks API - A high level introduction with examples
- MultiLabel Classification - Free Sound Audio and ATLAS Protein Classification (using four channel images)
@clck10 - Looking into fine_tune and general projects
- First part on learn.freeze
- Sanity checking fastai v2 data and models
- Complex-valued Parameter Initialization - Part 1
- Relearning to learn, deep.
- Building an image classifier using Fastai V2
- A look at Fastai’s ‘L’ data structure
- Improving upon flowers-102 baseline model
Using separate Transforms for your training and validation sets in fastai2 : goes deep into
split_idxusage inside of fastai2’s low-level Datablock API
- Medical Imaging using fastai : Reviewing fastai 60_medical_imaging notebook
- Starting with Medical Imaging Starter notebook that looks at some high level considerations when evaluating model results such as PPV, NPV, Specificity, Sensitivity
- Getting to know DICOMS : Taking a deeper look at how to view and manipulate DICOM images
- Image Augmentation
- Explore and clean your text data with UMAP clustering
- ICLR 2020 - Efficient NLP Transformer highlights
- ICLR 2020 - Efficient Deep Learning highlights
- Deep learning with galaxy images - my first blog post!
- Training a deep CNN to learn about galaxies in 15 minutes - a technical post about training CNNs for regression in astrophysics
- Visualizing CNNs, part 1 - exploring Pytorch/Fastai Hooks for visualizing CNN activations
- Visualizing CNNs, part 2 - implementing and understanding Grad-CAM for a galaxy classification problem
- Reconociendo dígitos en fastai2 -first blog post on how to use fastai2 for kaggle digits competition.
- Classifying cats and dogs using fast.ai’s vision library-First blog on image classification
Hannes (@ johannesstutz) Deep Learning Berlin
- Understanding fastai’s Midlevel API How to customize your data processing. Exploring Transforms, Pipelines, TfmdLists, Datasets
Blogs with General advice
- How to do machine learning efficiently
- Machine Learning and Testing
- How not to do fast.ai (or Any ML MOOC)
fastai2_extensions: Utilities for interpretation, exporting, and some augmentation. Link to forum post