Machine Learning with Python
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Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.

Admin: @HusseinSheikho || @Hussein_Sheikho
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🔖 637 interactive modules on ML and AI

On VizLearn, you can visually explore:
🫡 Gradient descent;
🫡 SVM and PCA;
🫡 Bayes' theorem;
🫡 BPE tokenization;
🫡 Query, Key, and Value;
🫡 KV cache;
🫡 Quantization;
🫡 Neural networks and LLMs.

Change the input data and immediately see the results of the calculations.

⛓️ Link to the tutorial
https://enghusseinsheikho.substack.com/p/637-interactive-modules-on-ml-and?r=3hwnr8&utm_campaign=post&utm_medium=web
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Forwarded from Data Analytics
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The 25 Best Free Resources for Learning AI in 2026

Learning artificial intelligence in 2026 is both easier and harder than it was a couple of years ago. Easier, because the best courses from Stanford and MIT, books by leading researchers, and hands-on lessons from Hugging Face are all openly available. Harder, because there is now far too much material, and the models and tools change every week. We have collected 25 proven free resources and arranged them by stage: from mathematics to LLMs, agents, and reading the latest papers.

Read: https://enghusseinsheikho.substack.com/p/the-25-best-free-resources-for-learning?r=3hwnr8&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true
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Forwarded from Machine Learning
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🔖 Interactive CNN Layer-by-Layer Explanation

With the CNN Explainer, you can learn about:
🫡 Input RGB channels;
🫡 Convolution;
🫡 ReLU;
🫡 Max Pooling;
🫡 Activation maps;
🫡 Flatten;
🫡 Softmax;
🫡 Final prediction.

You can upload your own image and see how the network processes it step by step.
⛓ https://poloclub.github.io/cnn-explainer/
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