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Was this email forwarded to you? Sign up here Hi there,A quick Monday note about our Twitter :) We share lots of helpful resources for your data science and ML journey. Free courses: CS109A Data Science course materials @Harvard are free and open for everyone!
1. Lecture notes
2. R code, Python notebooks
3. Lab material
4. Advanced sections
Learn here: harvard-iacs.github.io/2019-CS109A/pa… and books: A free book for you!
Fundamentals of Data Visualization by Claus O. Wilke
It's a guide to making visualizations that accurately reflect the data, tell a story, and look professional.
Read the open book here: clauswilke.com/dataviz/ and helpful lists: 5 self-supervised learning models, you should know about:
1. Wav2vec
2. BYOL
3. XLM-R
4. AVID
5. SEER
Find links and descriptions here: thesequence.substack.com/p/-edge137-sel… As well as our favorite ‘ML Research of the Week’: ML Research of this week:
1. @DeepMind AlphaFold DB vNext
2. @GoogleAI ML Code Completion
3. @AmazonScience Causal Inference and ML
Read more here: thesequence.substack.com/p/-deepminds-a… If you haven’t yet, please help us shape the ML value chain landscapeLet’s create an objective landscape of the ML Value Chain together. You’ve probably seen some AI/ML companies’ landscapes before. They are typically assembled by either analyst firms, media, or VC firms. But we trust that TheSequence’s audience only can shape an accurate landscape of the ML Value Chain. Participate and be the first to receive this super helpful research shaped by you! Many thanks 🧠 You’re on the free list for TheSequence Scope and TheSequence Chat. For the full experience, become a paying subscriber to TheSequence Edge. Trusted by thousands of subscribers from the leading AI labs and universities. |
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🔥 The PyTorch Foundation
Sunday, September 18, 2022
Weekly news digest curated by the industry insiders
📌 Event: Leverage your Snowflake, BigQuery, Redshift Data Warehouse with a Real-Time Feature Store / Sept 21
Friday, September 16, 2022
Building historical and reproducible training datasets from data warehouses
🗜🗜Edge#226: DeepSpeed Compression, a new library for extreme compression of deep learning models
Thursday, September 15, 2022
It combines compression and system optimization techniques for building smaller and more efficient deep learning architectures
🎙Or Itzary/Superwise About Model Observability and Streamlining Large ML Projects
Thursday, September 15, 2022
Getting to know the experience gained by researchers, engineers, and entrepreneurs doing real ML work is an excellent source of insight and inspiration. Share this interview if you like it. No
😶🌫️ Edge#225: Understanding Latent Diffusion Models
Tuesday, September 13, 2022
In this issue: we explain latent diffusion models; we discuss the original latent diffusion paper; we explore Hugging Face Diffusers, a library for state-of-the-art diffusion models. Enjoy the learning
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