A python package that consists of implementations of several neural networks and methods which assist in applying deep learning along with computer vision
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Updated
Mar 27, 2020 - Python
A python package that consists of implementations of several neural networks and methods which assist in applying deep learning along with computer vision
State-of-the-art 2D and 3D Face Analysis Project
This repo shows how to implement a training on CIFAR10 dataset with different Deep Learning frameworks: FastAI, JAX, Keras, MXNet, PaddlePaddle, Pytorch and Pytorch-lightning. An article was written to compare the ease of implementation (user friendly coding, ease of finding information online, etc.), time per epoch, memory and GPU usage, etc.
Character Embeddings Recurrent Neural Network Text Generation Models
Generate image features using resnetv2_18 from MXNet GluonCV
A deep learning model to detect passion fruit diseases, deployed to android
Lookahead Optimizer: k steps forward, 1step back for MXNet
A predictive model to detect wheather a bottle has a cap or not
Dive into Deep Learning: An interactive deep learning book with code, math, and discussions, based on the NumPy interface. [Fork from "d2l-ai/d2l-en" (www.d2l.ai). Translate to German? Adapt for use of Tensorflow (Lite)?]
This repository shows my history of MXNet learning.
Face Analysis Project on MXNet
Yet Another Machine Learning package for Chemistry
A Deep Learning model to detect passion fruit diseases, deployed to the cloud
Simple benchmarks on major deeplearning frameworks with Python.
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