Data Mining

Here's an interesting interview with Josh Dillon, who works on Tensorflow. In this video, he discusses working on the Distribution API, which is based on probabilistic programming. Watch this video to find out what exactly probabilistic programming is, where the use of Distributions and Bijectors comes into play, & how you can get started. Subscribe to our channel to stay up to date with Google Developers.

Medicine is ripe for disruption. The costs that result from poor quality trickle down to consumers and patients, who shoulder much of the burden of ever-increasing healthcare costs. In order to improve healthcare accessibility, the utilization of medical resources must be made more accurate, more efficient, and more secure. These technologies are blockchain and artificial intelligence. By utilizing the latest advancements in these technologies, the medical industry can improve quality, bring down cost, and democratize healthcare like never before.

Reliance is set to pick up a majority 72.69 percent stake in online education platform Embibe, which uses data analytics to deliver personalised learning outcomes to students. Reliance today agreed to invest the rupee equivalent of $180 million into Embibe, the Bengaluru-based AI education platform, over the next three years. A part of this will be towards acquiring a stake of 72.69 percent from Embibe's existing investors. The transaction is subject to customary closing conditions. This is one of the biggest transactions in the Indian education and deep technology space.

According to industry experts advances within artificial intelligence and automation will wipe out more than 50% of the jobs in the financial sector in the next 10 years however it is going to take some big investments to achieve automation at that scale. James D'Arezzo, CEO of Condusiv Technologies said, "Unless banks deal with the performance issues that AI will cause for ultra-large databases, they will not be able to take the money gained by eliminating positions and spend it on the new services and products they will need in order to stay competitive," he said. He also thinks that while hardware upgrades often solve these problems this comes hand in hand with sometimes inordinate expense with the Tokyo Institute of Technology Global Scientific and Computing Center as an example of this. The centre is on the verge of developing a supercomputer to meet the demands of artificial intelligence and big data applications. At the current cost of hardware, it would take around $50 – $100 Million dollars to build the supercomputer.

According to industry experts advances within artificial intelligence and automation will wipe out more than 50% of the jobs in the financial sector in the next 10 years however it is going to take some big investments to achieve automation at that scale. James D'Arezzo, CEO of Condusiv Technologies said, "Unless banks deal with the performance issues that AI will cause for ultra-large databases, they will not be able to take the money gained by eliminating positions and spend it on the new services and products they will need in order to stay competitive," he said. He also thinks that while hardware upgrades often solve these problems this comes hand in hand with sometimes inordinate expense with the Tokyo Institute of Technology Global Scientific and Computing Center as an example of this. The centre is on the verge of developing a supercomputer to meet the demands of artificial intelligence and big data applications. At the current cost of hardware, it would take around $50 – $100 Million dollars to build the supercomputer.

You are free to share this article under the Attribution 4.0 International license. A new computational model could help farmers and seedmakers take the guesswork out of what to plant each year. It's simple enough that a farmer could receive a recommendation containing the five best seed types to grow given the average yields, weather conditions, and soil composition of his or her region--ranked in order of simulated success rates. The program, dubbed SimSoy, uses tools as simple as a laptop, algorithms, and decision-making frameworks. "This could be done for any farm, and a wide variety of crops," says Durai Sundaramoorthi, senior lecturer in management at the Olin Business School at Washington University in St. Louis.

The following article is based on work done for my graduate thesis titled: Ethics and Bias in Machine Learning: A Technical Study of What Makes Us "Good," covering the limitations of machine learning algorithms when it comes to inclusivity and fairness. As Cathy O'Neil discusses in her book, Weapons of Math Destruction, the seeming impenetrability and absolute value of machine learning may not be all that we bargained for. Though machine learning appears to indisputably increase business value and efficiency, in some cases, it can sow inequality deeper by hard-coding it into our machines. It is imperative that machine learning experts, creators, and contributors account for "doing the right thing" as much as they do "meeting the bottom line" to balance the enormous power these mechanical decision makers possess. A machine learning algorithm is typically code written by a data scientist in a programming language such as R, Python, or Javascript.

SAN FRANCISCO--(BUSINESS WIRE)--The following is an opinion editorial provided by Navin Shenoy, executive vice president and general manager of the Data Center Group at Intel Corporation. In the wide world of big data, artificial intelligence (AI) holds transformational promise. Everything from manufacturing to transportation to retail to education will be improved through its application. But nowhere is that potential more profound than in healthcare, where every one of us has a stake. What if we could predict the next big disease epidemic, and stop it before it kills?

Companies looking to make good on the promise of machine learning for data analysis are turning to a somewhat unlikely old friend. Business intelligence systems, largely the domain for analyzing past performance, are being retrofitted with artificial intelligence to bring predictive features to their reporting capabilities. The Symphony Post Acute Network is one such organization. The health care company, which has 5,000 beds in 28 health care facilities in Illinois, Indiana and Wisconsin, wanted to use artificial intelligence and machine learning to improve care for up to 80,000 patients a year recovering from procedures like knee surgery, or receiving dialysis treatment. For example, buried deep in a patient's medical core could be an indication that a patient is particularly at risk for a dangerous fall and therefore requires extra precautions.

Not only can you follow the work happening in different domains, but you can also collaborate on multiple open source projects. All tech companies, from Google to Facebook, upload their open source project codes on GitHub so the wider coding / ML community can benefit from it. But, if you are too busy, or find following GitHub difficult, we bring you a summary of top repositories month on month. You can keep yourself updated with the latest breakthroughs and even replicate the code on your own machine! This month's list includes some awesome libraries.