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Friday, December 15, 2023

SE Radio 594: Sean Moriarity on Deep Studying with Elixir and Axon : Software program Engineering Radio

sean moriartySean Moriarity, creator of the Axon deep studying framework, co-creator of the Nx library, and writer of Machine Studying in Elixir and Genetic Algorithms in Elixir, printed by the Pragmatic Bookshelf, speaks with SE Radio host Gavin Henry about what deep studying (neural networks) means at present. Utilizing a sensible instance with deep studying for fraud detection, they discover what Axon is and why it was created. Moriarity describes why the Beam is good for machine studying, and why he dislikes the time period “neural community.” They focus on the necessity for deep studying, its historical past, the way it affords a very good match for a lot of of at present’s complicated issues, the place it shines and when to not use it. Moriarity goes into depth on a spread of subjects, together with get datasets in form, supervised and unsupervised studying, feed-forward neural networks, Nx.serving, choice timber, gradient descent, linear regression, logistic regression, help vector machines, and random forests. The episode considers what a mannequin seems to be like, what coaching is, labeling, classification, regression duties, {hardware} assets wanted, EXGBoost, Jax, PyIgnite, and Explorer. Lastly, they take a look at what’s concerned within the ongoing lifecycle or operational facet of Axon as soon as a workflow is put into manufacturing, so you may safely again all of it up and feed in new information.

This episode is sponsored by Miro.

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Tags: axon, beam, bumblebee, Choice Bushes, deep studying, elixir, erlang, EXGBoost, Gradient Descent, Jax, labeling, Linear Regression, Logistic Regression, machine studying, neural networks, nx, oban, PyIgnite, Random Forests, tensors

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