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.

Top 10 Python, AI and Machine Learning Open Source Projects

To become Data Scientists, you should know basics of some common machine learning algorithms, which would help to engage with a new-domain problem.

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…

Microsoft's latest AI-infused message is that Windows 10 Redstone 4 will give developers a unique AI platform. But what does this really mean?

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 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 post presents 5 practical resources for getting a start in natural language processing, covering a wide array of topics and approaches.

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.

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