One of the things that’s so fundamental in software development that it’s easy to overlook is the idea of a repository of shared code. As programmers, libraries immediately make us more effective. In…
Deep Learning methods achieve state-of-the-art results on a suite of natural language processing problems. What makes this exciting is that single models are trained end-to-end, replacing a suite of specialized statistical models.
Smart phones, smart TVs, smart cars. Machine everywhere are becoming more intelligent, and the manufacturing process itself (the smart factory) is not far behind the curve. In fact, predictions from business and IT experts are buzzing about the way in which IoT technologies are moving toward a revolution of the manufacturing industry. It will come ... Read more
In this blog post, I want to share the 8 neural network architectures from the course that I believe any machine learning researchers should be familiar with to advance their work.
Deep Learning gets more and more traction. It basically focuses on one section of Machine Learning: Artificial Neural Networks. This article explains why Deep Learning is a game changer in a
Artificial neural networks are computational models which work similar to the functioning of a human nervous system. There are several kinds of artificial neural networks. These type of netw
Summary: This is the first in a series about Chatbots. In this first installment we cover the basics including their brief technological history, uses, basic…
The Snips Embedded Voice Platform allows any device manufacturer to build a Private by Design voice interface to their product. It handles Wakeword Detection, Speech Recognition, and Natural Language Understanding
Today we are announcing integration of NVIDIA® TensorRTTM and TensorFlow. TensorRT is a library that optimizes deep learning models for inference and creates a runtime for deployment on GPUs in production environments. It brings a number of FP16 and INT8 optimizations to TensorFlow and automatically selects platform specific kernels to maximize throughput and minimizes latency during inference on GPUs. We are excited about the new integrated workflow as it simplifies the path to use TensorRT from within TensorFlow with world-class performance. In our tests, we found that ResNet-50 performed 8x faster under 7 ms latency with the TensorFlow-TensorRT integration using NVIDIA Volta Tensor Cores as compared with running TensorFlow only.
We take a look at the important things you need to know about sentiment analysis, including social media, classification, evaluation metrics and how to visualise the results.
We are pleased to announce the open sourcing of nGraph, a framework-neutral Deep Neural Network (DNN) model compiler that can target a variety of devices. With nGraph, data scientists can focus on data science rather than worrying about how to adapt their DNN models to train and run efficiently on different devices. Continue reading below [...]Rea
Using ML services, you can build first working models yielding valuable insights with a small team. Let’s have a look at the best machine learning platforms.
Machine Learning (ML) will become pervasive across all Data Centers services. Here, you’ll learn about ML Data Center workloads at Facebook and Google. My findings come from their own publications…
Machine Learning is currently dedicated to the completion of much more mundane tasks in a centerlised (almost all cases) with some exceptions it also runs on distributed infrastructure.In machine learning various specific algorithms and services are managed at the most efficient place between the actual sourc
This resource is designed primarily for beginner to intermediate data scientists or analysts who are interested in identifying and applying machine learning algorithms to address the problems of their interest.
This paper introduces the Artificial Intelligence (AI) community to TensorFlow* optimizations on Intel® Xeon® and Intel® Xeon Phi™ processor-based platforms.
Update (12/19/2017): other editions of this post: 2017, 2015. Last year, we did a recap with what we thought were the best Python libraries of 2015, which was widely shared within the Python community (see post in r/Python). A year has gone by, and again it is time to give due credit for the awesome work that has been done by the open source community this year. Again, we try to avoid most established choices such as Django, Flask, etc.
Microsoft is planning to include more artificial intelligence capabilities inside Windows 10 soon. The software giant is unveiling a new AI platform, Windows ML, for developers today, that wil
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