Artem Ryblov’s Data Science Weekly
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@artemfisherman’s Data Science Weekly: Elevate your expertise with a standout data science resource each week, carefully chosen for depth and impact.
Long-form content: https://artemryblov.substack.com
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The Illustrated Machine Learning

The idea is to make the complex world of Machine Learning more approachable through clear and concise illustrations.

The goal is to provide a visual aid for students, professionals, and anyone preparing for a technical interview to better understand the underlying concepts of Machine Learning.

Whether you're just starting out in the field or you're a seasoned professional looking to refresh your knowledge, these illustrations will be a valuable resource on your journey to understanding Machine Learning.

- Machine Learning
- Categorization
- Sampling and Resampling
- Bias/Variance
- Supervised Learning
- Unsupervised Learning
- Hyperparameters Tuning
- Machine Learning Engineering
- Introduction
- Before the Project Starts
- Data Collection and Preparation
- Projective Geometry
- Introduction
- Image Formation
- Structure from Motion
- Stereo Reconstruction
- Deep Learning Playbook

Link: https://illustrated-machine-learning.github.io/

Navigational hashtags: #armknowledgesharing #armtutorials
General hashtags: #machinelearning #ml #mlsystemdesign #machinelearningsystemdesign #geometry #visualization #illustrated #supervised #unsupervised #dl #deeplearning #bias #variance #biasvariance

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