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<div class="trigger"><a class="page-link" href="/narsil.github.io/about/">About Me</a><a class="page-link" href="/narsil.github.io/search/">Search</a><a class="page-link" href="/narsil.github.io/categories/">Tags</a></div> |
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<main class="page-content" aria-label="Content"> |
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<div class="home"><p>This is where I store what insights in ML and software dev I came across |
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and I felt compelled to properly structure my thought so I could at least |
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refer that to colleagues when poorly trying to explain them on the fly.</p> |
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<h1 id="posts">Posts</h1> |
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<ul class="post-list"><li><h3> |
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<a class="post-link" href="/narsil.github.io/ml/nlp/2020/07/22/creating-a-translate-app.html"> |
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Creating a dutch translation app |
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</a> |
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</h3><p class="post-meta-description">How to create a custom clone of translate.google.com</p><p class="post-meta">Jul 22, 2020</p> |
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</li><li><h3> |
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<a class="post-link" href="/narsil.github.io/energy/2020/03/19/solar-energy.html"> |
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Super simple estimation of available solar energy |
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</a> |
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</h3><p class="post-meta-description">How much energy is actually renewable and humanity's cap in consumption</p><p class="post-meta">Mar 19, 2020</p> |
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</li><li><h3> |
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<a class="post-link" href="/narsil.github.io/ml/2020/03/10/no-gd-training.html"> |
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Can we train neural networks without gradient descent ? |
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</a> |
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</h3><p class="post-meta-description">If the lottery ticket hypothesis is real, does that mean we can train a neural network without gradient descent?</p><p class="post-meta">Mar 10, 2020</p> |
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</li><li><h3> |
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<a class="post-link" href="/narsil.github.io/ml/docker/2020/03/04/running-gpu-enabled-docker.html"> |
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Running a docker with GPU enabled (for pytorch and tensorflow) |
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</a> |
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</h3><p class="post-meta">Mar 4, 2020</p> |
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</li><li><h3> |
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<a class="post-link" href="/narsil.github.io/ml/nlp/kldivergence/2020/02/26/self-kl-models.html"> |
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Self KL-divergence for detecting out of distribution data and unsupervised text classification |
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</a> |
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</h3><p class="post-meta-description">Running two models alongside each other for trivial out of distribution detection in production models and side bonus is getting unsupervised text classification</p><p class="post-meta">Feb 26, 2020</p> |
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</li><li><h3> |
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<a class="post-link" href="/narsil.github.io/ml/nlp/2019/08/06/model-based-bpe-encodings-3.html"> |
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Model based encodings (3) |
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</a> |
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</h3><p class="post-meta">Aug 6, 2019</p> |
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</li><li><h3> |
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<a class="post-link" href="/narsil.github.io/ml/nlp/2019/06/06/model-based-bpe-encodings-2.html"> |
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Model based encodings (2) |
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</a> |
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</h3><p class="post-meta">Jun 6, 2019</p> |
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</li><li><h3> |
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<a class="post-link" href="/narsil.github.io/ml/nlp/2019/05/16/model-based-bpe-encodings.html"> |
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Model based encodings |
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</a> |
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</h3><p class="post-meta-description">How to use BPE without this hardcoded algorithm</p><p class="post-meta">May 16, 2019</p> |
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