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I created a way to learn machine learning through Jupyter
2 projects | reddit.com/r/learnmachinelearning | 30 Apr 2021
There are actually some online books and courses built on Jupyter Notebook ([Dive to Deep Learning Book](https://github.com/d2l-ai/d2l-en) for example). However yours is more detail and could really helps beginners.
Trying to find resources for "Image Segmentation using RL"
2 projects | reddit.com/r/learnmachinelearning | 17 Nov 2021
Probably mean something like unet: https://github.com/milesial/Pytorch-UNet
How to add a pyramid pooling in UNet++?
2 projects | reddit.com/r/learnmachinelearning | 29 Mar 2021
Hi! I will give you some resources that might help you understand(I didnt implement a network but I can answer more questions about how you can train it). 1 This link gives you a broad explanation about UNet. 2 This is a link to a UNet used for binary segmentation. 3 This is a step by step guide. The UNet++ that I posted is good for multiclass segmentation. If you need more advice feel free to reply. Good luck!
What are some alternatives?
lightning-hydra-template - Deep Learning project template best practices with Pytorch Lightning, Hydra, Tensorboard.
muzero-general - MuZero
mmsegmentation - OpenMMLab Semantic Segmentation Toolbox and Benchmark.
segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.
unet-nested-multiple-classification - This repository contains code for a multiple classification image segmentation model based on UNet and UNet++
DeepADoTS - Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".
efficientdet-pytorch - A PyTorch impl of EfficientDet faithful to the original Google impl w/ ported weights
imbalanced-regression - [ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
ssd_keras - A Keras port of Single Shot MultiBox Detector
TF-Watcher - Monitor your ML jobs on mobile devices📱, especially for Google Colab / Kaggle
petastorm - Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.
ScanRefer - [ECCV 2020] ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language