libs.garden
Most popular libraries and apps
Categories
Deep Learning
larq/zookeeper β A small library for managing deep learning mo...
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A small library for managing deep learning models, hyper parameters and datasets
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plumerai/zookeeper
v0.2.1
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A small library for managing deep learning models, hyper parameters and datasets
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larq/zookeeper
v0.4.0
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Helper library for Chainer that makes managing and tracking deep learning experiments easy
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teffland/chainer-monitor
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Its a prototype of the general idea of quick managing of a Deep Learning project by choosing the best optimization algorithm in order to save time and resources lost due to poor decision of learning rate and choice of algorithm
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TheIndianCoder/Choose-the-best-Optimization-Algorithm-in-keras
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This repository is for managing the work of Udacity Nanodegree - Deep Learning Foundation.
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Eudie/Udacity-Deep_Learning_Foundation
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Tool for managing deep learning experiments
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nhynes/em
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The main goal of this project is to visualize data using big-data item "spark" and managing it "with SQLite". Creating a nice map with leaflet library that indicate the main terrorism attack all around the world and their descriptions. A descriptive plot for data viz of the general attack terrorism. Deep learning with network D3 library R to see the main target of terrorist group .
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mskanji/data_viz
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Deep Learning is one of the most highly sought after skills in tech. This is notebooks for newbie me who wanted to learn about deep learning or future me who might encounter an amnesia after time warping through super-symmetry-hyper-dimension space. This will help you, or at least myself, to become good again at Deep Learning.
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iqDF/100-days-DeepLearning
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Deep learning, architecture and hyper parameters search with genetic algorithms
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guybedo/minos
v0.4.3
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Frictionless Machine learning for growing teams. Your private Heroku for Deep Learning.
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hyper-ML/hyperflow
0.0.1
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Hyper-parameter Training in the "Deep Learning Tsunami"
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douxiaotian/heuristics_nn
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Automatic detection of Diabetic Retinopathy using Deep Learning. Net2net technique of architecture used for training fundus images dataset from Kaggle. VGG16 is used as the teacher model and a self constructed dilated convolution block is the student model. These two modules are concatenated and global average pool is applied to give final predictions. LAB format of images to split into 3 colour channels was used as preprocessing and Adaptive Histogram Equalisation to the L-channel applied before recombining into original RGB format. Hyper-parameters: Optimiser : Stochastic gradient descent with momentum 0.9 Loss Function : Categorical Crossentropy Learning Rate : 0.0001 which was reduced by a factor of 0.125 after 10 epochs Activation Function : ReLU for Conv layers and Softmax for output layer. Epochs : 20 Batch size : 32 Class Weight : Appropriate weightage applied while training according to dataset of each class as imbalance in dataset.
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sneha-gathani/Diabetic-Retinopathy-Detection
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Recent works have demonstrated that deep learning algorithms were very efficient to conduct security evaluations of embedded systems and had many advantages compared to the other methods. A comprehensive study of deep learning algorithms when applied in the context of side-channel analysis and we discuss the links with the classical template attacks. We address the question of the choice of the hyper-parameters for the class of multi-layer perceptron networks and convolutional neural networks. Several benchmarks and rationales are given in the context of the analysis of a masked implementation of the AES algorithm.
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NymeriaWang/DeepLearning_SCA_ASCAD
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R package for automatic hyper parameter tuning and ensembles with deep learning, gradient boosting machines, and random forests. Powered by h2o.
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andrewsommerlot/startml
v0.1.3
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Work for my master's thesis applying deep learning to the problem of hyper-spectral image classification
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hillelweintraub/deepLearn
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Forecasting Macroeconomic Parameters with Deep Learning Neural Networks - Final Year Peoject
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kokoff/deep-forecast
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TESTING DEEP LEARNING FOR DERIVING STELLAR ATMOSPHERIC PARAMETERS WITH EXTENDED MILES LIBRARY
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wangqixun/sage_sap
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A deep learning model to predict the parameters of the ellipse
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Golbstein/Deeplearning-Ellipse-Detection
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This project seeks to utilize Deep Learning models, LongShort Term Memory (LSTM) Neural Network algorithm to predict stock prices. We will use Keras to build a LSTM RNN to predict stock prices using historical closing price and trading volume and visualize both the predicted price values over time and the optimal parameters for the model.
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withharsh/Stock-Price-prediction-using-long-short-term-memory
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A helper allows you to manage your deep learning modelβs parameters in a convenient way.
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CaptainWilliam/Deep-Learning-Model-Saving-Helper
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This project seeks to utilize Deep Learning models, LongShort Term Memory (LSTM) Neural Network algorithm to predict stock prices. We will use Keras to build a LSTM RNN to predict stock prices using historical closing price and trading volume and visualize both the predicted price values over time and the optimal parameters for the model.
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harshithb/Stock-Price-prediction-using-long-short-term-memory
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This project seeks to utilize Deep Learning models, LongShort Term Memory (LSTM) Neural Network algorithm to predict stock prices. We will use Keras to build a LSTM RNN to predict stock prices using historical closing price and trading volume and visualize both the predicted price values over time and the optimal parameters for the model.
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Deekshant99/Stock-Market-Prediction-using-LSTM
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Small deep learning library for prototyping deep learning models in js.
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SemLaan/DeepPrototypeLibrary
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Mass Spectrometry for Small Molecules using Deep Learning
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brain-research/deep-molecular-massspec
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Deep learning based interesting&small class assignment
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weiyx16/Leaf-Classification-Segmentation
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Bring Deep Learning to small devices
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blue-oil/blueoil
v0.9.0
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A small convolution neural network deep learning framework implemented in c++.
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liugaolian/gordon_cnn
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tiny deep learning - a very small educational neural network simulator
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templeblock/tinydl
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MiniFlow : Small deep learning framework based on NumPy
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iuga/MiniFlow
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Small OpenCL based deep learning framework
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ALojdl/HastenedARMDeepLearning