| | Understanding Large Language Models – A Transformative Reading List (sebastianraschka.com) |
| 2 points by rasbt on Feb 7, 2023 | past |
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| | Four approaches to identifying AI-generated content (sebastianraschka.com) |
| 2 points by nemoniac on Feb 2, 2023 | past |
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| | What Are the Different Approaches for Detecting AI-Generated Content? (sebastianraschka.com) |
| 2 points by rasbt on Feb 1, 2023 | past |
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| | Comparing Different Automatic Image Augmentation Methods in PyTorch (sebastianraschka.com) |
| 1 point by rasbt on Jan 30, 2023 | past |
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| | Training factually correct LLMs requires vast amounts of factually correct data (sebastianraschka.com) |
| 1 point by rasbt on Jan 16, 2023 | past |
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| | Training an XGBoost Classifier Using Cloud GPUs Without Worrying Infrastructure (sebastianraschka.com) |
| 2 points by bilsbie on Jan 15, 2023 | past |
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| | Open Source Highlights 2022 for Machine Learning and AI (sebastianraschka.com) |
| 3 points by mariuz on Jan 6, 2023 | past |
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| | Machine Learning and AI Open Source Highlights 2022 (sebastianraschka.com) |
| 1 point by rasbt on Jan 5, 2023 | past |
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| | Influential Machine Learning Papers of 2022 (sebastianraschka.com) |
| 2 points by rasbt on Jan 3, 2023 | past |
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| | Noteworthy Deep Learning Papers of 2022 (sebastianraschka.com) |
| 1 point by rasbt on Jan 3, 2023 | past |
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| | Language Transformers, Fast and Slow (sebastianraschka.com) |
| 1 point by rasbt on Nov 7, 2022 | past |
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| | A Diffusion of Innovations – Some thoughts on the latest diffusion models (sebastianraschka.com) |
| 6 points by rasbt on Oct 12, 2022 | past | 1 comment |
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| | No, We Don't Have to Choose Batch Sizes as Powers of 2 (sebastianraschka.com) |
| 1 point by alexmolas on Oct 7, 2022 | past |
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| | A Short Chronology of Deep Learning for Tabular Data (sebastianraschka.com) |
| 148 points by tosh on Sept 4, 2022 | past | 14 comments |
|
| | A Short Chronology of Deep Learning for Tabular Data (sebastianraschka.com) |
| 1 point by sebg on Sept 1, 2022 | past | 1 comment |
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| | A Short Chronology of Deep Learning for Tabular Data (sebastianraschka.com) |
| 1 point by rasbt on July 24, 2022 | past |
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| | Matrix Cheatsheet for Matlab, Octave, Python NumPy, R and Julia (sebastianraschka.com) |
| 1 point by teleforce on July 20, 2022 | past |
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| | No, We Don't Have to Choose Batch Sizes as Powers of 2 (sebastianraschka.com) |
| 1 point by rasbt on July 5, 2022 | past |
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| | Sharing Deep Learning Research Models with Lightning: Leveraging the Cloud (sebastianraschka.com) |
| 1 point by rasbt on June 30, 2022 | past |
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| | Sharing Deep Learning Research Models: Building a Super Resolution App (sebastianraschka.com) |
| 3 points by sbbq on June 17, 2022 | past |
|
| | Taking Datasets, DataLoaders, and PyTorch’s New DataPipes for a Spin (sebastianraschka.com) |
| 2 points by rbanffy on June 17, 2022 | past |
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| | Taking Datasets, DataLoaders, and PyTorch’s New DataPipes for a Spin (sebastianraschka.com) |
| 2 points by sbbq on June 13, 2022 | past |
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| | Running PyTorch on the M1 GPU (sebastianraschka.com) |
| 92 points by my123 on May 21, 2022 | past | 42 comments |
|
| | Running PyTorch on the M1 GPU (sebastianraschka.com) |
| 2 points by sbbq on May 19, 2022 | past |
|
| | The key differences between Python 2.7.x and Python 3.x with examples (2014) (sebastianraschka.com) |
| 1 point by Tomte on May 16, 2022 | past |
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| | Creating Confidence Intervals for Machine Learning Classifiers (sebastianraschka.com) |
| 3 points by sbbq on April 25, 2022 | past | 1 comment |
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| | Machine Learning with PyTorch and Scikit-Learn (sebastianraschka.com) |
| 149 points by sbbq on Feb 25, 2022 | past | 38 comments |
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| | Machine Learning Vids on Tree-Based Methods, Model Eval, and Feature Selection (sebastianraschka.com) |
| 3 points by tbau50 on Dec 30, 2021 | past |
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| | The key differences between Python 2.7.x and Python 3.x with examples (2014) (sebastianraschka.com) |
| 1 point by Tomte on Sept 7, 2021 | past |
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| | Intro to Deep Learning (sebastianraschka.com) |
| 189 points by tbau50 on Aug 12, 2021 | past | 19 comments |
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| More |