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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…
Eric Muccino
Apr 13, 2020
Image Classification with Variable Input Resolution in Keras
Tutorial on how to set up and train a CNN for variable image resolution (Keras).
Eric Muccino
6
Mar 20, 2020
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…
Eric Muccino
Sep 10, 2019
Creating Custom Lambda Layers
Introduction:
Guru Prasad Natarajan
1
Sep 6, 2019
Deploying deep learning models on AWS lambda
About AWS Lambda
Guru Prasad Natarajan
2
Aug 30, 2019
Policy Assessment Using ML
Overview
Guru Prasad Natarajan
23
Aug 30, 2019
Generating Adversarial Samples in Keras (Tutorial)
Introduction
Eric Muccino
6
Aug 14, 2019
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…
Guru Prasad Natarajan
7
Jun 5, 2019
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…
Eric Muccino
27
Jun 5, 2019
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…
Eric Muccino
17
Jun 5, 2019

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