September 12, 2022

Week 36

5 Minutes of Data Science - week 36

Highlights from September 05 to September 11

Foreword

Hi folks!

Second week of the new format. A quick recap: github's trending repositories have a lot of diffusion-related content. Also exciting to know that DeepMind is exploring language models on confirmed veracity - models that only output content that is true.

Enjoy and see you next week.

Pedro

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Blogs

• My journey from DeepMind intern to mentor, by DeepMind
• In conversation with AI: building better language models, by DeepMind
• Learning to Walk in the Wild from Terrain Semantics, by Google AI
• A Multi-Axis Approach for Vision Transformer and MLP Models, by Google AI
• Digitizing Smell: Using Molecular Maps to Understand Odor, by Google AI
• Master’s student uses SURE opportunity to explore impact of machine learning, by Amazon Science
• Automatically optimizing execution of dynamic tensor operations, by Amazon Science
• Pinch-grasping robot handles items with precision, by Amazon Science
• A quick guide to Amazon’s 40-plus papers at Interspeech 2022, by Amazon Science
• Interspeech 2022, by Apple Machine Learning

Podcasts

• Zero-Cost Proxies: How to find the best neural network without training (Ep. 201), by Data Science At Home
• Fairness in e-Commerce Search, by Data Skeptic
• Ryan Fedasiuk - Can the U.S. and China collaborate on AI safety?, by Towards Data Science
• Licensing & automating creativity, by Practical AI
• Understanding Collective Insect Communication with ML, w/ Orit Peleg - #590, by The TWIML AI

Reddit

• Big brain time, at r/Data Science (💬69)
• Happy meme Monday, at r/Data Science (💬32)
• Here are the questions I was asked for my entry level DS job!, at r/Data Science (💬209)
• [P] Simple fastai based face restoration project, GitHub link in comments., at r/Machine Learning (💬34)
• [R] SIMPLERECON — 3D Reconstruction without 3D Convolutions — 73ms per frame !, at r/Machine Learning (💬24)
• [P] pytorch's Newest nvFuser, on Stable Diffusion to make your favorite diffusion model sample 2.5 times faster (compared to full precision) and 1.5 times faster (compared to half-precision), at r/Machine Learning (💬13)
• Fellow statisticians, how do you develop your reading comprehension in statistics? what are your learning strategies?, at r/Ask Statistics (💬17)
• What is the best way to explain the difference between Standard Deviation and Mean Absolute Deviation?, at r/Ask Statistics (💬19)
• Modeling for causal inference vs prediction, at r/Ask Statistics (💬29)
• AI Turns my Drawings into Pure Art || Stable Diffusion Drawing App, at r/Latest in ML (💬0)
• General Video Recognition with AI (How AI Understands Videos), at r/Latest in ML (💬1)

Github jupyter notebook trends

• CompVis/stable-diffusion: A latent text-to-image diffusion model
• openai/CLIP: Contrastive Language-Image Pretraining
• alexeygrigorev/mlbookcamp-code: The code from the Machine Learning Bookcamp book and a free course based on the book
• altryne/sd-webui-colab: A repo for the maintenance of the Colab version of stable-diffusion-webui repo
• alembics/disco-diffusion:
• CompVis/latent-diffusion: High-Resolution Image Synthesis with Latent Diffusion Models
• meituan/YOLOv6: YOLOv6: a single-stage object detection framework dedicated to industrial applications.
• CompVis/taming-transformers: Taming Transformers for High-Resolution Image Synthesis
• rinongal/textual_inversion:
• Stability-AI/stability-sdk: SDK for interacting with stability.ai APIs (e.g. stable diffusion inference)
• kaieye/2022-Machine-Learning-Specialization:
• dennybritz/reinforcement-learning: Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
• rasbt/python-machine-learning-book-3rd-edition: The "Python Machine Learning (3rd edition)" book code repository
• google-research/google-research: Google Research
• DataTalksClub/mlops-zoomcamp: Free MLOps course from DataTalks.Club
• fivethirtyeight/data: Data and code behind the articles and graphics at FiveThirtyEight
• xuebinqin/DIS: This is the repo for our new project Highly Accurate Dichotomous Image Segmentation
• ageron/handson-ml2: A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
• WongKinYiu/yolov7: Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
• jakevdp/PythonDataScienceHandbook: Python Data Science Handbook: full text in Jupyter Notebooks
• nianticlabs/monodepth2: [ICCV 2019] Monocular depth estimation from a single image
• MorvanZhou/PyTorch-Tutorial: Build your neural network easy and fast, 莫烦Python中文教学

Github python trends

• AUTOMATIC1111/stable-diffusion-webui: Stable Diffusion web UI
• sd-webui/stable-diffusion-webui: Stable Diffusion web UI
• xinntao/Real-ESRGAN: Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
• hpcaitech/ColossalAI: Colossal-AI: A Unified Deep Learning System for Big Model Era
• vinta/awesome-python: A curated list of awesome Python frameworks, libraries, software and resources
• python-poetry/poetry: Python dependency management and packaging made easy.
• TencentARC/GFPGAN: GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
• karpathy/minGPT: A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
• impira/docquery: An easy way to extract information from documents
• microsoft/unilm: Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
• kakaobrain/coyo-dataset: COYO-700M: Large-scale Image-Text Pair Dataset
• alibaba/EasyCV: An all-in-one toolkit for computer vision
• tiangolo/fastapi: FastAPI framework, high performance, easy to learn, fast to code, ready for production
• eloialonso/iris: Transformers are Sample Efficient World Models
• geohot/tinygrad: You like pytorch? You like micrograd? You love tinygrad!
• WZMIAOMIAO/deep-learning-for-image-processing: deep learning for image processing including classification and object-detection etc.
• PaddlePaddle/PaddleOCR: Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)
• apache/airflow: Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

See you next week!