Deep Learning Framework built entirely using numpy
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Updated
May 28, 2021 - Python
Deep Learning Framework built entirely using numpy
Deep Learning Algorithms implemented from scratch using Numpy
a lightweight deep-learning framework with ruby
Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code.
DLEC - Deep Learning Emotion Classifier
This Repository contains the most important parts of my Capstone Project. The project was to build and then compare the performance of traditional ML Algorithms to Deep Learning Algorithms on text data. I learned a lot about Natural Language Processing. Compiled all my findings in a 30-page report as well as my power point presentation.
A simple NumPy-based deep learning framework. Create and train neural networks easily, experiment with backpropagation, optimization, and explore the code to grasp the inner workings.
This is a mini Deep learning framework that supports automatic differentiation.
An all-in-one Docker image for deep learning. Contains all the popular DL frameworks (TensorFlow, Theano, Torch, Caffe, etc.)
Super Simple AI framework!
My custom deep learning experimental platform. This template supports automated custom deep learning model training and record the results.
natural language processing utilities for agnostic framework
customized darknet (origin: https://github.com/pjreddie/darknet)
Numpy Neural Nets - a simple Deep Learning framework built on top of numpy.
Custom deep learning library for backpropagation across arbitrary architectures using pure NumPy
Custom deep learning framework with CuDNN
Starter Pack for creating fast responsive Web App for Fast.AI Vision models
A micro-framework for building a handwritten text recognition (HTR) system
This project was to create a neural network that will predict the coefficients for the potential function of Silicon crystals.
Purely NumPy based API for building deep neural networks.
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