MIT's introductory course on deep learning methods with applications in game play, and more!

(Starting March 11th 2022)

http://introtodeeplearning.com/

#deeplearning


For previous years videos you can check their youtube channel:
https://www.youtube.com/playlist?list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI


Team
@data_enthusiasts
@OpenArchiveBooks

Make a Fair Coin from a Biased Coin (2018)

https://www.xarg.org/2018/01/make-a-fair-coin-from-a-biased-coin/

Team
@data_enthusiasts
@OpenArchiveBooks

🦾 Test Suites for Validating ML Models & Data

Github: https://github.com/deepchecks/deepchecks

Example: https://docs.deepchecks.com/en/stable/examples/guides/quickstart_in_5_minutes.html

Docs: https://docs.deepchecks.com/

Paper: https://arxiv.org/pdf/2203.08491v1

Blog: https://deepchecks.com/blog/

Team
@data_enthusiasts
@OpenArchiveBooks

🎨 Pastiche Master: Exemplar-Based High-Resolution Portrait Style Transfer

Github: https://github.com/williamyang1991/DualStyleGAN

Paper: https://arxiv.org/pdf/2203.13248v1

Video: https://www.youtube.com/watch?v=scZTu77jixI

Project: https://www.mmlab-ntu.com/project/dualstylegan/

Dataset: https://paperswithcode.com/dataset/ffhq

Team
@data_enthusiasts
@OpenArchiveBooks

🌟 Parametric Distributionally Robust Optimization

Github: https://github.com/pmichel31415/P-DRO

Paper: https://arxiv.org/pdf/2204.06340v1

Datasett: https://paperswithcode.com/dataset/celeba

Team
@data_enthusiasts
@OpenArchiveBooks

🔗 Unsupervised Image-to-Image Translation with Generative Prior

A novel framework GP-UNIT, to improve the overall quality and applicability of the translation algorithm

Github: https://github.com/williamyang1991/gp-unit

Paper: https://arxiv.org/pdf/2204.03641v1

Datasett: https://paperswithcode.com/dataset/celeba-hq

Team
@data_enthusiasts
@OpenArchiveBooks

🔹 Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval

Github: https://github.com/xiaoyuan1996/AMFMN

Paper: https://arxiv.org/pdf/2204.09868v1

Dataset: https://paperswithcode.com/dataset/kitti

Team
@data_enthusiasts
@OpenArchiveBooks

🔝 OPT (Open Pre-trained Transformers) is a family of NLP models trained on billions of tokens of text obtained from the internet.

175B GPT-3

Github: https://github.com/facebookresearch/metaseq

Instructions: https://github.com/facebookresearch/metaseq/blob/main/docs/setup.md

Paper: https://arxiv.org/pdf/2205.01068v2

Dataset: https://paperswithcode.com/dataset/superglue

Team
@data_enthusiasts
@OpenArchiveBooks

Hugging Face released a new free course on Deep Reinforcement Learning.

Course has good combination of theory and practical exercises.

Course link: https://github.com/huggingface/deep-rl-class

Team
@data_enthusiasts
@OpenArchiveBooks

⚡️ EmotionFlow: Capture the Dialogue Level Emotion Transitions

Code: https://github.com/fpcsong/emotionflow

Paper: https://arxiv.org/pdf/2204.10298v1

Dataset: https://paperswithcode.com/dataset/meld

Team
@data_enthusiasts
@OpenArchiveBooks

Efficient and performance-portable vector software

CPUs provide SIMD/vector instructions that apply the same operation to multiple data items. This can reduce energy usage e.g. fivefold because fewer instructions are executed. We also often see 5-10x speedups.

Code: https://github.com/google/highway

Paper: https://arxiv.org/pdf/2205.05982v1

Testing: https://github.com/google/highway/blob/master/g3doc/release_testing_process.md

Team
@data_enthusiasts
@OpenArchiveBooks

Important machine learning concepts through visual essays in a fun, informative, and accessible manner by Amazon

#machinelearning #beginners

https://mlu-explain.github.io/

Team
@data_enthusiasts
@OpenArchiveBooks

📝 Automated Crossword Solving

Pretrained models, precomputed FAISS embeddings, and a crossword clue-answer dataset.

Github: https://github.com/albertkx/berkeley-crossword-solver

Paper: https://arxiv.org/pdf/2205.09665v1

Dataset: https://www.xwordinfo.com/JSON/

Team
@data_enthusiasts
@OpenArchiveBooks

Learning Python Pandas

#Pandas #pd

Team
@data_enthusiasts
@OpenArchiveBooks

🟢 Green Hierarchical Vision Transformer for Masked Image Modeling

Github: https://github.com/layneh/greenmim

Paper: https://arxiv.org/pdf/2205.13515v1

Dataset: https://paperswithcode.com/dataset/coco

Team
@data_enthusiasts

🔻 AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition

Github: https://github.com/ShoufaChen/AdaptFormer

Paper: https://arxiv.org/pdf/2205.13535v1

Dataset: https://paperswithcode.com/dataset/something-something-v2

Team
@data_enthusiasts

🎆 Optimizing Relevance Maps of Vision Transformers Improves Robustness

This code allows to finetune the explainability maps of Vision Transformers to enhance robustness.

Github: https://github.com/hila-chefer/robustvit

Colab: https://colab.research.google.com/github/hila-chefer/RobustViT/blob/master/RobustViT.ipynb

Paper: https://arxiv.org/pdf/2206.01161

Dataset: https://github.com/UnsupervisedSemanticSegmentation/ImageNet-S

Team
@data_enthusiasts

Team
@data_enthusiasts
@OpenArchiveBooks

⛩ XBound-Former: Toward Cross-scale Boundary Modeling in Transformers

Github: https://github.com/naiyugao/panopticdepth

Paper: https://arxiv.org/pdf/2206.00806v1

Dataset: https://paperswithcode.com/dataset/kvasir-seg

Team
@data_enthusiasts
@OpenArchiveBooks

#beginner #datascience #careerpath

Team
@data_enthusiasts
@OpenArchiveBooks