Strategies, standards, and supporting resources to help you make the Web more accessible to people with disabilities. After recently deciding to learn Web Development as well as Data Science, this section of the introductory course really grabbed my attention.

NVIDIA and VMware today announced their intent to deliver accelerated GPU services for VMware Cloud on AWS to power modern enterprise applications, including AI, machine learning and data analytics workflows. These services will enable customers to seamlessly migrate VMware vSphere-based applications and containers to the cloud, unchanged, where they can be modernized to take advantage of high-performance computing, machine learning, data analytics and video processing applications. Increasingly businesses are applying artificial intelligence (AI) technologies to differentiate and advance their processes and offerings. Enterprises are rapidly adopting AI(1) and implementing new AI strategies that require powerful computers to create predictive models from petabytes of corporate data. Across industries, enterprises are implementing machine learning applications such as image and voice recognition, advanced financial modeling and natural language processing using neural networks that rely on NVIDIA GPUs for faster training and real-time inference.

App-only fintech startup Monzo is scaling up its machine learning capabilities and plugging employees into the rich stream of data generated by 1.7m global users as it forges ahead of the high-street banks in the digital space. Neal Lathia, data scientist and machine learning lead at the UK-based bank, told The Drum how his team is delivering "incremental gains" in the app, in customer and the product using smarter automation since he took the role on one year ago. Lathia, previously lead data science at SkyScanner, commands a team of more than 20 people. When he joined there were only two. Now he is looking to harness the wealth of data at the company's disposal to get Monzo "working faster". It contrasts with the role a data scientist at a high street bank may have, weighed down by legacy systems, corporate baggage and sheer scale.

VMworld--NVIDIA and VMware today announced their intent to deliver accelerated GPU services for VMware Cloud on AWS to power modern enterprise applications, including AI, machine learning and data analytics workflows. These services will enable customers to seamlessly migrate VMware vSphere-based applications and containers to the cloud, unchanged, where they can be modernized to take advantage of high-performance computing, machine learning, data analytics and video processing applications. Increasingly businesses are applying artificial intelligence (AI) technologies to differentiate and advance their processes and offerings. Enterprises are rapidly adopting AI(1) and implementing new AI strategies that require powerful computers to create predictive models from petabytes of corporate data. Across industries, enterprises are implementing machine learning applications such as image and voice recognition, advanced financial modeling and natural language processing using neural networks that rely on NVIDIA GPUs for faster training and real-time inference.

Over the past few years, the delivery services in India has witnessed a massive growth. Today, we have a delivery service for every task -- whether you want to order food, get something delivered to one point to another in a city etc. However, there was a small void in this sector as well (for every task there is a different app) until Dunzo came into the scenario. Founded in 2014 by Mukund Jha, Kabeer Biswas, Dalvir Suri, and Ankur Agarwal, Dunzo in recent times has gained a significant amount of traction in the industry. Dunzo is an on-demand delivery service platform has changed the way people move things, shop and commute.

Bruno Aziza is a technology entrepreneur. He has focused on scaling businesses and turning them into global leaders. Bruno has helped lead startups, medium and large-size organizations across the US, France, the UK and Germany. Some of them include Microsoft, Apple, and...

Here's why Intel just offered $15.3 billion for Mobileye, an Israeli company that specializes in machine vision and learning for cars. The automobile is being dismantled, reimagined, and rebuilt in Silicon Valley. Intel's proposed $15.3 billion acquisition of Mobileye, an Israeli company that supplies carmakers with a computer-vision technology and advanced driver assistance systems, offers a chance to measure the scale of this rebuild. In particular, it shows how valuable on-the-road data is likely to be in the evolution of automated driving. While the price tag might seem steep, especially with so many players in the automated driving space today, Mobileye has some key technological strengths and strategic advantages.

As talk of AI and machine learning permeates our world, the benefits for businesses are getting lost in a sea of technical jargon and prognostication by experts from all walks of life. At the end of the day, data is the fuel for any machine learning algorithm and it's common for the terms used to describe how that data is used to become confusing. As folks who love data, machines, and especially people, we decided to put together a helpful guide to machine learning and the terms that businesses should know as they look to navigate this exciting and complex frontier of technological advancement.

The automobile is being dismantled, reimagined, and rebuilt in Silicon Valley. Intel's proposed $15.3 billion acquisition of Mobileye, an Israeli company that supplies carmakers with a computer-vision technology and advanced driver assistance systems, offers a chance to measure the scale of this rebuild. In particular, it shows how valuable on-the-road data is likely to be in the evolution of automated driving. While the price tag might seem steep, especially with so many players in automated driving today, Mobileye has some key technological strengths and strategic advantages. It's also developing new technologies that could help solidify this position.

Over 1.5 million people are diagnosed with cancer each year in America alone. Indeed, research currently relies on data from just 3% of patients. MIT's Regina Barzilay is hoping to rectify that. Via the MIT Stata Center, she leads a Machine Learning-based project that aims to derive insight from patient data. She's working with a consortium of partners, including Massachusetts General Hospital (MGH) to bring data science to clinical research.