rcurtin_irc changed the topic of #mlpack to: mlpack: a scalable machine learning library (https://www.mlpack.org/) -- channel logs: https://libera.irclog.whitequark.org/mlpack -- NOTE: messages sent here might not be seen by bridged users on matrix, gitter, or slack
<zoq[m]> > <@_slack_mlpack_U04R0CDBSFJ:matrix.org> Greetings!
<zoq[m]> Hello, thanks for the interest, an important first step is to get familiar with the codebase, e.g. by using mlpack, reading the code and perhaps you can find an interesting issue to solve.
<zoq[m]> > I am Ansh Kanotra, an undergraduate in Electronics and Communications Engineering at BITS Hyderabad. I am very interested in Machine Learning, Deep Learning and the math behind all of it, including linear algebra and probability. As i looked through the previous ideas page, the one on reinforcement learning and Improvization on ANN Modules interested me the most. Therefore please let me know how to advance into these topics 🙂
<zoq[m]> https://www.mlpack.org/gsoc.html has some additional information
<rcurtin[m]> shenzhiy21 (Ceeeb): sorry for the slow response; from the command-line, `mlpack_knn` has the `--epsilon` option that you can use for approximate kNN. In addition the `kNN` class has an `epsilon` argument in the [constructor](https://github.com/mlpack/mlpack/blob/master/src/mlpack/methods/neighbor_search/neighbor_search.hpp#L86) that can be used for approximate kNN 👍️
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<ShivyaGarg[m]> Hi everyone,
<ShivyaGarg[m]> Hope you all are doing well! My name is Shivya Garg and I am currently pursuing my Bachelor's degree in Artificial Intelligence. I have keen interest in machine learning, deep learning and data science. I am keen to contribute to the mlpack open source community. However, since I am new to this, I could use some guidance. Would anyone be willing to help me get started with my open source journey?
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