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🏥Self-supervised Learning for Medical images

Due to standard imaging procedures, medical images (X-ray, CT scans, etc) are usually well aligned.
This paper gives an opportunity to utilize such an alignment to automatically connect similar pairs of images for training.

Code: https://github.com/fhaghighi/TransVW
Paper: https://arxiv.org/pdf/2102.10680

#biolearning #medical #dl #pytorch #keras

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😃 GoEmotions: A Dataset for Fine-Grained Emotion Classification

Github: https://github.com/google-research/google-research/tree/master/goemotions

Google AI: https://ai.googleblog.com/2021/10/goemotions-dataset-for-fine-grained.html

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Introduction to Linear Algebra for Machine Learning with Python.

Very specific to what you need. Nothing more, and nothing less.

One of the best guides I've found online.
https://pabloinsente.github.io/intro-linear-algebra

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https://youtu.be/Xw-zxQSEzqo

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Good repository of ML notes

#beginner #datascience #machinelearning

https://chrisalbon.com/

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The Age of AI by Henry Kissinger, Eric Schmidt and Daniel Huttenlocher

https://www.economist.com/books-and-arts/2021/11/20/henry-kissinger-and-eric-schmidt-take-on-ai

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Acquisition of Chess Knowledge in AlphaZero

69-pages paper of analysis how #AlphaZero plays chess. TLDR: lots of concepts self-learned by neural network can be mapped to human concepts.

This means that generally speaking we can train neural networks to do some task and then learn something from them. Opposite is also true: we might imagine teaching neural networks some human concepts in order to maek them more efficient.

Post: https://en.chessbase.com/post/acquisition-of-chess-knowledge-in-alphazero
Paper: https://arxiv.org/pdf/2111.09259.pdf

#RL

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Some random topics to know about

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The Most In-Demand Skills for Data Scientists in 2021
#beginner #datascience #machinelearning

https://www.kdnuggets.com/2021/04/most-demand-skills-data-scientists.html

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Intro to AI Ethics

https://www.kaggle.com/learn/intro-to-ai-ethics

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BodyPix: Real-time Person Segmentation in the Browser with TensorFlow.js

Released BodyPix 2.0 with #multiperson support and improved accuracy (based on ResNet50), a new API, weight quantization, and support for different image sizes with TensorFlow.js

It estimates and renders person and body-part segmentation at 25 fps on a 2018 15-inch MacBook Pro, and 21 fps on an iPhone X.

code: https://github.com/tensorflow/tfjs-models/tree/master/body-pix
demo: https://storage.googleapis.com/tfjs-models/demos/body-pix/index.html
blog: https://blog.tensorflow.org/2019/11/updated-bodypix-2.html

#dl #segmentation

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Probabilistic Machine Learning - Philipp Henning 2021

Summer Term 2021 at the University of Tübingen.
YouTube Playlist topics covering probabilistic ML topics Gaussian Distributions, Markov Chain Montecarlo etc..
🎥🔗LINK🔗
🖥Slides: LINK

#freecourse #machinelearning #university

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Transferable Interactiveness Knowledge for Human-Object Interaction Detection

Paper:
https://arxiv.org/pdf/1811.08264.pdf

Github:
https://github.com/DirtyHarryLYL/Transferable-Interactiveness-Network

Learning list:
https://github.com/DirtyHarryLYL/HOI-Learning-List

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Mathematics for Machine Learning

This is a 400-page free book about the mathematics needed for machine learning. It covers the things you need to know in order to get started with machine learning.


Website: https://mml-book.github.io/
PDF: https://mml-book.github.io/book/mml-book.pdf

#ML #Mathematics #FreeBook

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An overview of the fundamental data science/AI libraries:

• numpy is the quintessential library for scientific computing in Python, in that in supports high-performance arithmetic in batches via its array data structure.
• pandas builds on numpy in that it supports SQL-style manipulation of tabular data.

Numpy and pandas encourage you to conceptualize your data as "one thing". Unlike the rest of Python, writing "explicit" for loops for numpy and pandas operations is actually less communicative than using the provided functions and methods (which are optimized), and should be avoided as much as possible.

• sklearn has general-purpose machine learning tools as well as ready-made implementations of popular algorithms that you can fit to your data.
• scipy implements functions that are useful for scientific computing that aren't found in numpy.
• matplotlib is used for data visualization.
• PyTorch and Tensorflow are both used for deep learning that can benefit from GPU computation.

#python #libraries #DS #AI #ML #DL

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🎼 Music Classification: Beyond Supervised Learning, Towards Real-world Application

📖 Book

💻Code

📜 Paper

📝Dataset

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All the Made With ML fundamentals & MLOps lessons are released!

- ✅ 47 lessons, 100% free
- 🏆 26K+ GitHub ⭐️
- ❤️ 30K+ community
- 🛠 Project-based
- 💻 Intuition & application (code)


https://madewithml.com/


Who is this course for?
- 💻 Software engineers / Data scientists looking to learn how to responsibly create ML systems.
- 🎓 College grads looking to learn the practical skills they'll need for the industry.
- 🚀 Product Managers who want to develop a technical foundation.
#freecourse #machinelearning #mlops

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Timers and Such: A Practical Benchmark for Spoken Language Understanding with Numbers

End-to-end pipeline for Spoken Language Understanding (SLU)

Paper:
https://arxiv.org/pdf/2104.01604v1.pdf

Github:
https://github.com/speechbrain/speechbrain/tree/develop/recipes/timers-and-such

Dataset:
https://zenodo.org/record/4623772#.YHFLkxKRWJk

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