There are still plenty of people out there in search of the perfect match, but the dating app Hater, which matches people based on the things they mutually dislike, has discovered an interesting trend among its users. There weren't always enough users in any given region, so the app expanded the radius for people in those areas, allowing users to start matching all over the globe. One recent survey found that more than 90 percent of college students are using dating apps for purposes other than hooking up or finding love -- mainly they're there for entertainment and the ego boost you get from being "liked." In an effort to capitalize on this, Bumble added BumbleBFF in early 2016, and Tinder launched Tinder Social a year ago.
The four project teams are lead by Kripa Varanasi of the Department of Mechanical Engineering, Randy Kirchain and Jeremy Gregory of the Concrete Sustainability Hub, Lisa Anderson of the Department of Chemical Engineering, and Danielle Dahan of the Center for Energy and Environmental Policy Research. Water recapture at MIT's power plant Department of Mechanical Engineering Associate Professor Kripa Varanasi is receiving funding to test a water recapture device developed by his research group, installing it on the MIT Central Utilities Plant (CUP) cooling towers. Two research scientists in the MIT Concrete Sustainability Hub, Jeremy Gregory and Randy Kirchain, are receiving funding to implement a quantitative approach to evaluating the life cycle economic and environmental impacts of proposed new buildings on campus. Danielle Dahan, a graduate research assistant at the Center for Energy and Environmental Policy Research, is receiving funding to collaborate with Professor Christopher Knittel of MIT Sloan, Wade Berner of MIT Facilities, and undergraduate Manuel Mundo to investigate the effectiveness of the fault detection and diagnostic (FDD) software used by MIT and other universities to prevent energy waste in HVAC systems.
On 1st of August 2017, we will start a free online training program for Machine Learning, called Machine Learning Army Camp. We will integrate the knowledge from 20 books into a single big knowledge network, and you will get to see how it will grow over time. In ML Army Camp we will build one big network specifically for Machine Learning. Short info about me: Machine Learning is my primary interest in life, and in my book called "Machine Learning God" I explain why I chose Machine Learning, and then of course I continue with technical treatment of the subject matter.
Chances are, you've already encountered artificial intelligence today. Did your email spam filter keep junk out of your inbox? We constantly hear that we're on the verge of an AI revolution, but the technology is already everywhere. And Coursera co-founder Andrew Ng predicts that smart technology will help humans do even more.
But it raises huge questions for companies and workers who face the challenges – and opportunities – of digital disruption. Just look at WoWooHR, a Chinese company that started offering social insurance management through an online HR platform – and serves enterprises with a highly efficient and high quality "Internet-Plus" HR Service. Using mobile online technology, big data management and cloud platforms, WoWooHR aims to provide any employee, in any company in even the remotest corners of China, with professional, efficient and high quality HR services. Of course, the opportunities provided by digital sustainability go much further.
About this course: This 1-week accelerated on-demand course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities. At the end of this course, participants will be able to: • Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform • Use CloudSQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform • Employ BigQuery and Cloud Datalab to carry out interactive data analysis • Choose between Cloud SQL, BigTable and Datastore • Train and use a neural network using TensorFlow • Choose between different data processing products on the Google Cloud Platform Before enrolling in this course, participants should have roughly one (1) year of experience with one or more of the following: • A common query language such as SQL • Extract, transform, load activities • Data modeling • Machine learning and/or statistics • Programming in Python Google Account Notes: • You'll need a Google/Gmail account and a credit card or bank account to sign up for the Google Cloud Platform free trial (Google is currently blocked in China).
There's no doubt about it - Data Science is big news right now. We decided to share this resource with you, and so here are Udemy's top selling courses. These are the courses that are in Udemy's top selling list over the past 90 days, but also mostly make the list in every update. These are the new courses (only a couple of months old) that have made it into Udemy's top selling list of the past 90 days.
Editor's note: The following is an interview with leading authority on marketing research and Distinguished University Professor Michel Wedel, of the University of Maryland, conducted by marketing scientist Kevin Gray, in which Wedel concisely outlines the current state of the field. Michel Wedel: Marketing analytics involves the examination of data about how customers feel, act, and interact around products and services, using descriptive, diagnostic, and predictive metrics and mathematical methods. Marketing analytics is increasingly interdisciplinary, combining methods from business, mathematics, statistics, econometrics, psychometrics, and computer science. MW: Marketing analysts typically work at the interface of statistics, computer science, and marketing, and they need to have broad and deep skills.
The Department of ICT has several large and active research groups in Information and Communication Technology including 12 Professors, 15 Associate Professors, 10 Assistant professors and about 15 Research Fellows on the PhD programme in ICT. The department has successfully led a number of large research projects funded by the Research Council of Norway; the EU research programmes FP7 and H2020, as well as national and international industries. Within these strategic research areas, CAIR researchers head or contribute to a number of research projects, funded by the Research Council of Norway and EU research programmes. The responsibilities of the open professor position include: a) research and PhD/master's student supervision in the area of machine learning, and b) teaching on artificial intelligence (theory, algorithms and implementation) at the master's and PhD level.
Massive Open Online Courses (MOOCs) are a good starting point, with a lot to offer. The article entitled "Top Machine Learning MOOCs and Online Lectures: A Comprehensive Survey" lists a number of good resources. For example, the MXNet website lists a number of data set sources for CNNs and RNNs. Intel's Python-based Neon framework from Nervana, now an Intel company, supports platforms like Apache Spark, TensorFlow, Caffe, and Theano.