pennylane
ivy
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pennylane | ivy | |
---|---|---|
2 | 1 | |
2,113 | 10,475 | |
2.7% | - | |
9.8 | 10.0 | |
4 days ago | almost 1 year ago | |
Python | Python | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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pennylane
ivy
-
Need internship/part time role in AI/ML/Data Science field.
As a volunteer developer at Ivy, I also been actively contributing to the project for several months now. I extended the Ivy Functional API by adding some linear algebra functions - matrix_exp (https://github.com/ivy-dl/ivy/blob/dev/ivy/linalg/matrix_exp.py) and diff (https://github.com/ivy-dl/ivy/blob/dev/ivy/linalg/diff.py) - to all four popular deep learning frameworks: NumPy, TensorFlow, PyTorch, and JAX. These functions allowed developers to perform matrix exponentiation and differentiation operations more efficiently and easily using any of these frameworks.
What are some alternatives?
qiskit-ibm-provider - Qiskit Provider for accessing the IBM Quantum Services: Online Systems and Simulators
machine_learning_refined - Notes, examples, and Python demos for the 2nd edition of the textbook "Machine Learning Refined" (published by Cambridge University Press).
ADCME.jl - Automatic Differentiation Library for Computational and Mathematical Engineering
tensorboardX - tensorboard for pytorch (and chainer, mxnet, numpy, ...)
Cirq - A python framework for creating, editing, and invoking Noisy Intermediate Scale Quantum (NISQ) circuits.
foolbox - A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
tensor-sensor - The goal of this library is to generate more helpful exception messages for matrix algebra expressions for numpy, pytorch, jax, tensorflow, keras, fastai.
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
leptonai - A Pythonic framework to simplify AI service building
PDEBench - PDEBench: An Extensive Benchmark for Scientific Machine Learning