Distributed Deep Learning with Elephas
This posts follow from the setup of the master slave cluster using Apache Spark (here) Considering your Spark environment is ready, we can make use of Elephas library to develop…
Biomedical image analysis: Segmentation, datasets, metrics and loss functions
Biomedical image analysis The success of deep learning in image analysis has encouraged the biomedical imaging researchers to investigate its potential in analyzing various medical modalities to aid clinicians in…
Optimizers, Learning Rates and Callbacks
What is covered? Types of optimizers and learning ratesKeras callbacks and checkpoints like early stopping, adjusting learning rates, etc. Types of optimizers and adaptive learning methods Optimizers In neural networks…
Visualizing Deep Learning: Filter, Class Activation Maps and LIME
What is covered? OverviewImporting librariesLoading the MNIST datasetPreprocessingLoading the trained modelEvaluationModel visualizationFilter visualizationClass activation mapLIMEConclusion Overview Unlike machine learning models, the deep learning models lack transparency in the decision making…
Building First CNN Model
What is covered? OverviewDatasetImporting the librariesLoading the datasetSetting data shapeOne hot encodingBuilding and compiling the modelCallbacksTraining and visualizing the modelVisualize model output Overview This post covers the development of handwritten…
Overview of Deep Learning Basics – III
What is covered? Overfitting and underfittingRegularizationDropoutVanishing and exploding gradientWeights intialization Overfitting and underfitting During training, a neural network undergoes many epochs (may be more than 100 or 500) to learn…
Master-Slave Setup using Apache Spark on Windows 10 with Ubuntu Subsystem
What is covered? OverviewInstalling python in windows sub-system (Ubuntu 16.04)Installing Apache spark in windows sub-system (Ubuntu 16.04)Master/Slave configurationStart spark clusterStop spark clusterTest the cluster setup Overview Windows 10 offers an…
Overview of Deep Learning Basics – II
Convolution Neural Network OverviewConvolution layerActivation layerPooling layer Overview Among the various deep learning models such as stacked auto-encoders [1], deep Boltzmann machines [2], deep conventional extreme learning machines [3], deep…
Overview of Deep Learning Basics – I
What is covered? IntroductionPerceptronNeural networkActivation functionLoss functionGradient descentSummaryRecommended resources Prologue Deep learning is a form of machine learning that uses a model of computing that mimics the structure of the…