Deep Learning Guides, Tutorials, Research, and Use-Cases

HACKER’S GUIDE TO NEURAL NETWORKS, #2

Deep Learning Modeling Machine Learning|Neural Networksposted by Andrej Karpathy March 29, 2017

Chapter 2: Machine Learning In the last chapter we were concerned with real-valued circuits that computed possibly complex expressions of their inputs (the forward pass), and also we could compute the gradients of these expressions on the original inputs (backward pass). In this chapter we will... Read more

TensorFlow and Queues

Deep Learning Modeling Python|TensorFlowposted by Aaron Schumacher March 29, 2017

There are many ways to implement queue data structures, and TensorFlow has some of its own. FIFO Queue with a list In Python, a list can implement a first-in first-out (FIFO) queue, with slightly awkward syntax: >>> my_list = >>> my_list.insert(0, 'a') >>> my_list.insert(0, 'b')... Read more

Algorithms are Black Boxes, That is Why We Need Explainable AI

Deep Learning Modeling Tools & Languages AI|Algorithmsposted by Mark van Rijmenam March 28, 2017

Artificial Intelligence offers a lot of advantages for organisations by creating better and more efficient organisations, improving customer services with conversational AI and reducing a wide variety of risks in different industries. Although we are only at the beginning of the AI revolution that is upon us, we... Read more

Deep Learning, IoT Sensor Data…and Bats!

Deep Learning Modeling Deep Learning|IoTposted by Sean Lorenz March 28, 2017

At the very center of Internet of Things excitement is the sensor. Not just one sensor, mind you, but a sensor that normally would just be sending a data stream to who knows where would now have access to the information from another sensor measuring something... Read more

Attention and Memory in Deep Learning and NLP

Deep Learning Modeling NLP/Text Analyticsposted by Denny Britz December 27, 2016

A recent trend in Deep Learning are Attention Mechanisms. In an interview, Ilya Sutskever, now the research director of OpenAI, mentioned that Attention Mechanisms are one of the most exciting advancements, and that they are here to stay. That sounds exciting. But what are Attention Mechanisms?... Read more

Productionizing Deep Learning from the Ground Up – Adam Gibson ODSC Boston 2015

Conferences Deep Learning Modeling ODSC East 2015|Speaker Slidesposted by Open Data Science June 15, 2015

Productionizing Deep Learning From the Ground Up from odsc Presenter Bio Adam Gibson is the founder of Skymind.io and is a deep learning specialist based in San Francisco assisting Fortune 500 companies, hedge funds, PR firms and startup accelerators with their machine learning projects. Adam has... Read more

Recurrent Neural Networks for Text Analysis – Alec Radford ODSC Boston 2015

Conferences Deep Learning Modeling NLP/Text Analytics ODSC East 2015|Speaker Slidesposted by Open Data Science June 3, 2015

Recurrent Neural Networks for Text Analysis from odsc Recurrent Neural Networks hold great promise as general sequence learning algorithms. As such, they are a very promising tool for text analysis. However, outside of very specific use cases such as handwriting recognition and recently, machine translation, they... Read more

Scalable Data Science and Deep Learning with H2O – Arno Candel ODSC Boston 2015

Conferences Deep Learning Modeling Tools & Languages Workflow ODSC East 2015|Speaker Slidesposted by Open Data Science June 2, 2015

Scalable Data Science and Deep Learning with H2O from odsc The era of Big Data has passed, and the era of sensory overload – that is, the proliferation of sensor data – is upon us. The challenge today is how to create the next generation of... Read more

DIY Deep Learning with Caffe Workshop – Kate Saenko ODSC Boston 2015

Conferences Deep Learning Modeling Tools Tools & Languages ODSC East 2015|Speaker Slidesposted by Open Data Science June 2, 2015

DIY Deep Learning with Caffe Workshop from odsc Caffe (Convolutional Architecture for Fast Feature Embedding) is a deep learning framework made with expression, speed, and modularity in mind. It is developed by the Berkeley Vision and Learning Center (BVLC) and by community contributors. Caffe’s expressive architecture... Read more