DOCS . JAX . DEV {}

Matching Content Categories {📚}

• Telecommunications
• Video & Online Content
• Technology & Computing

Content Management System {📝}

What CMS is docs.jax.dev built with?

Custom-built

No common CMS systems were detected on Docs.jax.dev, but we identified it was custom coded using Bootstrap (CSS).

Traffic Estimate {📈}

What is the average monthly size of docs.jax.dev audience?

🚀 Good Traffic: 50k - 100k visitors per month


Based on our best estimate, this website will receive around 50,153 visitors per month in the current month.

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How Does Docs.jax.dev Make Money? {💸}

We can't see how the site brings in money.

While profit motivates many websites, others exist to inspire, entertain, or provide valuable resources. Websites have a variety of goals. And this might be one of them. Docs.jax.dev might be plotting its profit, but the way they're doing it isn't detectable yet.

Keywords {🔍}

jax, function, jit, automatic, functions, import, compilation, def, return, differentiation, vmap, installation, numpy, runs, timeit, transformation, justintime, check, loop, std, dev, loops, quickstart, key, numbers, cpu, gpu, transformations, jaxjit, operations, products, batched, vectorization, advanced, guides, tpu, builtin, arrays, python, familiar, array, alpha, random, randomnormalkey, jaxgrad, grad, eps, arbitrarily, reversemode, composed,

Topics {✒️}

reverse-mode vector-jacobian products forward-mode jacobian-vector products array-oriented numerical computation promote matrix-vector products advanced autodiff operations performs automatic differentiation full jacobian matrix matrix-matrix products numpy api automatic differentiation transformations reverse-mode jax vector-valued functions scalar-valued functions batch-aware version forward-mode jax arrays representing batches call %timeit selu_jit natively vectorized version à la numpy typical numpy programs extra batch dimension essential jax features timing represents execution avoid explicit looping automatic differentiation primitives jax internals python package index jacrev def hessian jax import jacfwd generate random numbers pip install jax sharp bits 🔪 reverse-mode automatic vectorization jax features built pytrees introduction jax runs transparently apply_matrix function maps import numpy pseudorandom numbers import jax installation jax open xla efficiently map specific case _ = selu_jit random numbers batch dimension pip install auto-vectorization

External Links {🔗}(5)

• What is the monthly revenue of https://github.com/jax-ml/jax?
• What's the revenue for https://numpy.org/?
• What's https://github.com/openxla's gross income?
• How much money does https://pypi.org/project/jax/ generate?
• What's the profit of https://en.wikipedia.org/wiki/Automatic_differentiation?

Libraries {📚}

• Bootstrap
• Clipboard.js
• Typed.js

Emails and Hosting {✉️}

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