this project is a lightweight autograd engine built using numpy
and python, designed to mimic pytorch's functionality. it
supports scalar and tensor operations, activation functions,
deep learning layers, optimizers, and loss functions, with
plans for future feature expansion. currently, it includes
essential operations like matrix multiplication, backpropagation,
convolution, and optimizers like adam and sgd, with tests
available to demonstrate its functionality.

this project, is a basic c implementation of numpy-like array
operations, offering multi-dimensional array support and functions
for scientific computing. it includes core array manipulation
features like mathematical operations, reshaping, and matrix
multiplication. users can create, manipulate, and perform
operations on arrays, similar to python's numpy, with support for
random arrays, trigonometric functions, and linear algebra operations.

Ever feel that your dataset is too small? Use neuaug, a tool
for generating augmented data for image and text processing.

here i implement research papers and deep learning concepts over
time. i have solved few papers so far, and will keep track of more
as i progress. links to the research papers will be attached as
they are completed.