They say great data is 95% of the problem in machine learning. We saw first hand at Udacity that this is the case, with the amazing reception from the machine learning community when we open sourced over 250GB of driving data. But, finding interesting data is really hard, and actively holds the industry back from progress. In trying to learn more about this problem I searched far and wide, and cataloged just a sliver of the datasets I found. In the hope that others might find this catalog useful, here's 20 weird and wonderful datasets you could (perhaps) use in machine learning.

Human resources departments rarely, if ever, are thought of as cutting edge when it comes to the use of technology. A closer look, however, shows the implementation of new technologies, including solutions powered by Artificial Intelligence (AI), in almost every aspect of the talent function. According to a recent Towers Watson HR Service Delivery and Technology Survey, HR professionals are overhauling structure to improve quality and efficiency with 33% of the group spending significantly more on technology in the last year. HR's investment in new technology has also spurred the creation of new data sources. Data around employee productivity, wellness, manager effectiveness, and a host of other activities is quickly dwarfing the traditional data set that HR has traditionally been using.

The results of Tuesday's US election shocked many--including pollsters and campaign insiders. As a result, many have begun questioning the data and methods behind predictions, wondering what went wrong. But not everyone got it wrong: An AI tool created by an Indian startup in Mumbai in 2004 has correctly predicted the last three US elections, including this one. By collecting and analyzing 20 million social media data points, MogIA, developed by Sanjiv Rai, has used sentiment to determine political outcomes. And social media has proven to have a powerful impact on candidates' popularity.

Wipro Cited as a Leader in Service Providers for Next-generation Oracle Application Projects by Leading Independent Research and Advisory Firm Business Wire India Wipro Ltd. (NYSE: WIT, BSE: 507685, NSE: WIPRO), a leading global information technology, consulting and business process services company today announced that Wipro has been cited as a "Leader" by technology global research and advisory firm Forrester Research Inc. in its report, 'The Forrester Wave(TM): Services Providers for Next-Generation Oracle Application Projects, Q3 2016'. Forrester evaluated 13 service providers across three categories of current offering, strategy and market presence. Forrester wrote, "Wipro is a proven provider making big investments in the shift to cloud. It has a long track record of delivering Oracle services ... [Wipro] was recognized by Oracle with a co-innovation award at Oracle's Collaborate conference in 2016." According to the Forrester report: "Wipro wants to be the partner of choice for tomorrow's digital businesses; it has invested in its own artificial intelligence tool, [Wipro HOLMES Artificial Intelligence Platform(TM)], and in next-generation Oracle technologies. Wipro has recently started to invest in digital experience and customer journey mapping capabilities, including its acquisition of Designit and associated studios."

With Google, Microsoft and Facebook all pushing artificial intelligence, AI is becoming the next battleground for agencies, perpetually on the hunt for new service lines. AI basically gives machines the ability to think like humans. A simple example: You can have a one-on-one conversation with another person, but AI can talk to 500 people at the same time and make decisions based on real-time data to learn what's going on in each conversation, explained Dave Meeker, vp of Isobar's U.S. operations. In the context of advertising and marketing, AI theoretically means more personalized and interactive consumer experience, including targeted programmatic ad buys, identification of site visitors' decision-making patterns, conversational commerce like bots, as well as smarter search and recommendation engines on websites, according to six agency executives interviewed for this article. At the moment, with the help of AI developed by big tech companies, agencies are able to serve cognitive ads and integrate voice-activated assistants in their campaigns.

Artificial Intelligence evokes a whole gamut of reactions. The cinematic world has been taking unrestrained creative liberty for ages. Such ambiguities that hound artificial intelligence (AI) clearly stem from an inherent lack of understanding of its root concepts. Interestingly, in one form or the other, the human race is already surrounded with AI. The era of Artificial Intelligence has begun. The truest form of AI is referred to as Strong AI or True AI, which is the stage when machines can behave as skillfully and flexibly as humans.

Many rural Ugandans don't have Internet access, and the radio is a central source of news -- and platform for citizens' opinions. Many rural Ugandans don't have Internet access, and the radio is a central source of news -- and platform for citizens' opinions. The inspiration for the tool came from projects that use social media to identify citizens' concerns -- for instance, what concerns people have about an immunization drive, or how often they suffer power outages. But at the Global Pulse lab in Kampala, Uganda, social media analysis wouldn't work, says lab manager Paula Hidalgo-Sanchis -- especially if the U.N. wanted to listen to rural voices.

Graphics chipmaker Nvidia blew past its third quarter earnings targets Thursday after the bell. The company posted record-revenue for the quarter, thanks to strong sales of Nvidia's new Pascal GPUs. Nvidia co-founder and CEO Jen-Hsun Huang said the GPUs are fully ramped and rolling out in gaming, VR, self-driving cars and datacenter AI computing applications. "We have invested years of work and billions of dollars to advance deep learning. Our GPU deep learning platform runs every AI framework, and is available in cloud services from Amazon, IBM, Microsoft and Alibaba, and in servers from every OEM. GPU deep learning has sparked a wave of innovations that will usher in the next era of computing," he said.

Facebook has succeeded in transmitting data at almost 20Gbps between two towers in Southern California in tests of a technology key to its plans to deliver internet service to rural areas using drones. The tests were conducted earlier this year and made use of frequencies in the so-called E-band, a group of millimeter wave frequencies between 60 and 90GHz. Such signals are capable of high-bandwidth data transmission but are susceptible to attenuation from distance, weather, and obstacles, so they are typically used for short-range, point-to-point transmissions. Facebook used a 60-centimeter dish to send data over a 13-kilometer link between Malibu and Woodland Hills. That test initially shot data at between 100Mbps and 3Gbps and allowed engineers to collect transmission data on clear days and during clouds, fog, high winds, and rain, Facebook said in a Thursday blog post.

I have been using Lean Six Sigma (LSS) to improve business processes for the past 10 year and am very satisfied with its benefits. Recently, I've been working with a consulting firm and a software vendor to implement a machine learning (ML) model to predict remaining useful life (RUL) of service parts. The result which I feel most frustrated is the low accuracy of the resulting model. As shown below, if people measure the deviation as the absolute difference between the actual part life and the predicted one, the resulting model has 127, 60, and 36 days of average deviation for the selected 3 parts. I could not understand why the deviations are so large with machine learning.