Week 51 - now with feeds from data science newsletters!
5 Minutes of Data Science - week 51
Highlights from December 19 to December 25
Foreword
Happy holidays everyone! 🎄
First and foremost: newsletters are here! That means I'm including the feeds for various data science newsletters. I've been gradually adding them - feel free to reach out if you want a specific newsletter to be included. Right now, I'm only adding RSS-capable newsletters.
Also, plenty of goodies all around, especially the github trends. Check them out below👇
Come say hi on Mastodon. See you next week!
Blogs
- Recent honors and awards for Amazon scientists, by Amazon Science
- AmazonNext program hosts final project presentations at Virginia HQ2, by Amazon Science
- Auto-translating "Dive into Deep Learning" with Amazon Translate, by Amazon Science
- Popular deep-learning book from Amazon authors gets update, by Amazon Science
- Nine teams selected for Alexa Prize SocialBot Grand Challenge, by Amazon Science
- How a lifelong music student uses melody and lyrics in TTS research, by Amazon Science
- Controlling formality in machine translation, by Amazon Science
Newsletters
- Last Week in AI: How GPT learns to reason, Waymo expands to all of SF, Artists can opt-out from Stable Diffusion 3, and more!, by Last Week in AI
Podcasts
- Geospatial Machine Learning at AWS with Kumar Chellapilla, by The TWIML AI
- Real-Time ML Workflows at Capital One with Disha Singla, by The TWIML AI
Youtube
- Prof. MURRAY SHANAHAN - Consciousness, Embodiment, Language Models, by Machine Learning Street Talk
- SARA HOOKER - Fairness, Interpretability, Language Models, by Machine Learning Street Talk
- HATTIE ZHOU - Teaching Algorithmic Reasoning via In-context Learning #NeurIPS, by Machine Learning Street Talk
- Job hunt results as a mid-level Data Scientist w/ ADHD, at r/Data Science (💬202)
- Agree?, at r/Data Science (💬54)
- Got my first Data Science job!!!, at r/Data Science (💬81)
- [R][P] I made an app for Instant Image/Text to 3D using PointE from OpenAI, at r/Machine Learning (💬40)
- Trippy Inkpunk Style animation using Stable Diffusion [P], at r/Machine Learning (💬14)
- [Discussion] Anyone else having a hard time not getting mad/cringing at the general public anthropomorphizing the hell out of chatGPT?, at r/Machine Learning (💬307)
- How can I determine which input variables are important for predicting the output?, at r/Ask Statistics (💬7)
- How to avoid the frustration of learning theoretical statistics?, at r/Ask Statistics (💬8)
- Studying statistics or economics?, at r/Ask Statistics (💬25)
- Automatic Re-Aging with AI! Disney’s FRAN Model Explained, at r/Latest in ML (💬1)
Github jupyter notebook trends
- annotated_deep_learning_paper_implementations: 🧑🏫59 Implementations/tutorials of deep learning papers with side-by-side notes📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...),🎮reinforcement learning (ppo, dqn), capsnet, distillation, ...🧠
- data-engineering-zoomcamp: Free Data Engineering course!
- ML-For-Beginners: 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
- Data-Science-For-Beginners: 10 Weeks, 20 Lessons, Data Science for All!
- whisper: Robust Speech Recognition via Large-Scale Weak Supervision
- stable-diffusion-webui-colab: stable diffusion webui colab
- pytorch-deep-learning: Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
- fastbook: The fastai book, published as Jupyter Notebooks
- tensorflow-deep-learning: All course materials for the Zero to Mastery Deep Learning with TensorFlow course.
- zero-to-mastery-ml: All course materials for the Zero to Mastery Machine Learning and Data Science course.
- Machine-Learning-Specialization-Coursera: Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
- notebooks: Jupyter notebooks for the Natural Language Processing with Transformers book
- AI-For-Beginners: 12 Weeks, 24 Lessons, AI for All!
- coursera-deep-learning-specialization: Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Network…
- codespaces-jupyter: Explore machine learning and data science with Codespaces
- DeepLearningSystem: Deep Learning System core principles introduction.
- micrograd: A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
- pytorch-Deep-Learning: Deep Learning (with PyTorch)
- Data-science: Collection of useful data science topics along with code and articles
Github python trends
- CodeGeeX: CodeGeeX: An Open Multilingual Code Generation Model
- black: The uncompromising Python code formatter
- dream-textures: Stable Diffusion built-in to the Blender shader editor
- openai-cookbook: Examples and guides for using the OpenAI API
- unilm: Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
- ultimatevocalremovergui: GUI for a Vocal Remover that uses Deep Neural Networks.
- pyChatGPT: An unofficial Python wrapper for OpenAI's ChatGPT API
- yfinance: Download market data from Yahoo! Finance's API
- erpnext: Free and Open Source Enterprise Resource Planning (ERP)
- CodeFormer: [NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer
- openai-python: None
- chatgpt-clone: Build Yo'own ChatGPT with OpenAI API & Gradio
- RL4LMs: A modular RL library to fine-tune language models to human preferences
- DALL-E: PyTorch package for the discrete VAE used for DALL·E.
- OpenCore-Legacy-Patcher: Experience macOS just like before
- public-apis: A collective list of free APIs
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