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Case Studies, Insights, and Discussions of our Modernization Efforts.​

Improving Classification Accuracy with ACGAN (Keras)
Supervised machine learning uses labeled data to train models for classification or regression over a set of targets. The performance of a…
Image Classification with Variable Input Resolution in Keras
Tutorial on how to set up and train a CNN for variable image resolution (Keras).
Visualizing How Convolution Neural Networks “See”
Convolution Neural Networks (CNN) are a class of neural network architecture that are designed to learn image recognition tasks in a way…
Creating Custom Lambda Layers
Deploying deep learning models on AWS lambda
About AWS Lambda
Policy Assessment Using ML
Generating Adversarial Samples in Keras (Tutorial)
Serving machine learning models using TensorFlow Serving
This post is a continuation of the previous post where we deployed a machine learning application using Docker, Flask, ngnix and gunicorn…
Convolutional Generative Adversarial Network: “EyeGaze” Image Generator
A generative adversarial network (GAN) is a system composed of two neural networks: a generator and a discriminator. The discriminator…
Active Learning for Fast Data Set Labeling
Active learning is a special case of machine learning where a model can query a user for input. In this post, we will see how we can use…

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