Stream Data Processing with Apache Kafka and TensorFlow
Editor’s note: Yong is a speaker for the upcoming ODSC East 2019 this April 30 – May 3! Be sure to check out his talk, “Deep Learning for Real Time Streaming Data with Kafka and TensorFlow.” As one of the most popular deep learning frameworks, TensorFlow has been used... Read more
From the New York Times to NASA: How Text Analysis Saves Lives
Editor’s note: Alex is a presenter for ODSC East 2019 this April 30 – May 3! Be sure to check out his talk, “From the New York Times to NASA: How Text Analysis Saves Lives.” Machine learning techniques are driving disruptive change across disparate fields in engineering. A parallel,... Read more
Deep Learning with Reinforcement Learning
Reinforcement learning (RL) is an area of machine learning that employs an autonomous agent that learns to perform a task by trial and error without any guidance from a human. A system of rewards and penalties compels the machine to solve a problem independently. Human involvement is limited to altering... Read more
Deep Learning for Text Classification
Matt will be presenting more on Ulmfit at ODSC East 2019 this May! Check out his talk “State of the Art Text Classification with ULMFiT” there. The rise of the internet has led to a faster flow of information, where news posted to a relatively obscure blog can be... Read more
Deep Learning for Business: 5 Use Cases
Enterprises at every stage of growth from startups to Fortune 500 firms are using AI, machine learning, and deep learning technologies for a wide variety of applications. Deep learning, as the fastest growing area in AI, is empowering much progress in all classes of emerging markets and ultimately will... Read more
The Beginners Guide for Video Processing with OpenCV
Computer vision is a huge part of the data science/AI domain. Sometimes, computer vision engineers have to deal with videos. Here, we aim to shed light on video processing – using Python, of course. This might be obvious for some, but nevertheless, video streaming is not a continuous process,... Read more
Deep Learning Finds Fake News with 97% Accuracy
In his article published on opendatascience.com in 2017, George McIntire describes an experiment building a “fake news” classifier using a document-vector model and Naive Bayes approach. He reports an 88% accuracy when classifying a “fake news” dataset which he assembled from various sources. This of course immediately made me wonder if deep neural networks (DNNs)... Read more
Going to the Bank: Using Deep Learning For Banking and the Financial Industry
At ODSC London 2018, Pavel Shkadzko explained to the audience how Gini GmbH, where he works as a semantics engineer, uses deep learning to automate information extraction from financial documents, such as invoices. By applying deep learning to tasks historically handled by optical character recognition and clever regular expression... Read more
Create Your First Face Detector in Minutes Using Deep Learning
Face detection is one of the most widely-demanded subfields of computer vision. Due to the advent of deep learning, computer vision has gained significant development in the last few years, and this trend is only going to increase over time. There are more and more people using computer vision... Read more
New Approaches Apply Deep Learning to Recommender Systems
Oliver Gindele is Head of Machine Learning at Datatonic. At ODSC Europe 2018, he spoke about how to apply deep learning techniques to recommender systems. He discussed how data scientists can implement some of these novel models in the TensorFlow framework, starting from a collaborative filtering approach and extending... Read more