Finding bottlenecks in applications -- an example
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Updated
Dec 21, 2015 - Java
Finding bottlenecks in applications -- an example
Term 2 Project 1 Dog Breed Classifier and human face detector using ImageNet, superhuman CNNs, and Haar Cascades
🔧 Performance Optimization Project - Simulated real-world scenario where a Desktop VR application must be optimized for release
99.7% accuracy solution for Dogs vs Cats Redux Kaggle competition
A Keras implementation of YOLOv3 (Tensorflow backend)
single-file "bottle.py" , a website-application µ framework
Logs times of page creations and intermediate results to spot bottlenecks in Islandora stack.
A small experiment with convolutional neural network in keras.
Visualize the Latent Space of an Autoencoder using matplotlib
DenseNet implementation in Keras
simple ABM program to simulate a moving danger (e.g., fire) and people in a confined space trying to escape the danger
Autoencoder dimensionality reduction, EMD-Manhattan metrics comparison and classifier based clustering on MNIST dataset.
Autoencoder dimensionality reduction, EMD-Manhattan metrics comparison and classifier based clustering on MNIST dataset
Generate labels for (wine) bottle neck
A PyTorch toolkit for 2D Human Pose Estimation.
Leibniz is a python package which provide facilities to express learnable partial differential equations with PyTorch
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