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TensorFlow and Queues
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
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!
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
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
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
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
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
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