Using SAS Optimization with Python and containers
A simple example of how you can combine SAS and open-source technologies to solve real business issues.
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Convolutional Neural Networks: Briefly
Neural networks, particularly convolutional neural networks, have become more and more popular in the field of computer vision. What are convolutional neural networks and what are they used for?
Bayesian optimization in SAS
Learn how Bayesian optimization works through a simple demo.
Sentiment Analysis using DeepRNN Action Set
In this blog, I use a Recurrent Neural Network (RNN) to predict whether opinions for a given review will be positive or negative. This prediction is treated as a text classification example. The Sentiment Classification Model is trained using deepRNN algorithms and the resulting model is used to predict if new reviews are positive or negative.
Using optimization to define weights and parameters for customer risk rating models
Customer risk rating models play a crucial role in complying with the Know Your Customer (KYC) and Customer Due Diligence (CDD) requirements, which are designed to assess customer risk and prevent fraud. Today, the most common form of the Customer Risk Rating model is a score-based risk rating model. This
Building a YOLO object detection model using SAS
Computer vision is one of the most sought-after artificial intelligence (AI) applications today, finding a wide variety of use cases in image recognition, object detection, biomedical assessment, and more. SAS supports a diverse set of AI and deep learning capabilities that can be used in many of these applications. One
Demo of deep learning to detect tumors in liver CT scans
This is the fifth and final post in my series of posts about the deep learning model I developed to detect tumors in 3D CT scans of livers. My last post talked about visualizing the results of the computer vision project. This post will cover model accuracy and the final
SAS deep learning with Python made easy using DLPy
I look forward to Pi Day every year at SAS because it's a day of celebration including yummy pies and challenging games that challenge you to recall the digits after the decimal point in Pi. Plus you get to wear Pi t-shirts (I have about seven). Today, though we are going to talk about DLPy which sounds like Pi and
Refining a deep learning model for object detection
This is the fourth post in my series about a computer vision project I worked on to identify liver tumors in CT scans. In my previous post, I had taken a break from my deep learning model to work on data management and data labeling. Now, I’ll return to the
Constructing the front of the computer vision pipeline
This is the third post describing a computer vision project I worked on at SAS to identify liver tumors in CT scans. In my previous post I talked about testing different models and hyperparameters for the models. Today, I’ll talk about data processing for image data. If you need to