Deep learning is an area of machine learning that has become ubiquitous with artificial intelligence. The complex, brain-like structure of deep learning models is used to find intricate patterns in large volumes of data. These models have heavily improved the performance of general supervised models, time series, speech recognition, object
Tag: neural networks
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.
According to the World Cancer Research Fund, Breast cancer is one of the most common cancers worldwide, with 12.3% of new cancer patients in 2018 suffering from breast cancer. Early detection can significantly improve treatment value, however, the interpretation of cancer images heavily depends on the experience of doctors and technicians. The
What is object detection? Object detection, a subset of computer vision, is an automated method for locating interesting objects in an image with respect to the background. For example, Figure 1 shows two images with objects in the foreground. There is a bird in the left image, while there is a dog
In my 25 years at SAS, I‘ve noticed the continued use of important algorithms, such as logistic regression and decision trees, which I’m sure will continue to be steady staples for data scientists. After all, they’re easy-to-use, interpretable algorithms. However, they’re not always the most accurate and stable classifiers. To
On the first day of Big Data Analytics my colleagues sent to me: A data scientist discussing a decision tree On the second day of Big Data Analytics my colleagues sent to me: Two business analysts and A data scientist discussing a decision tree On the third day of Big Data Analytics my
At the KDD conference this week I heard a great invited presentation called How to Create a $1 billion Model in 20 days: Predictive Modeling in the Real World – A Sprint Case Study. It was presented by Tracey de Poalo from Sprint and former Kaggle President and well known