Finally, a comprehensive hands-on machine learning course with specific focus on regression based models for the investment community and any passionate investors. In the past few years, there has been a massive adoption and growth in the use of data science, artificial intelligence and machine learning to find alpha. However, information on and application of machine learning to investment are scarce. This course has been designed to address that. It is meant to spark your creative juices.

Some big trends have emerged this week in red hot areas like blockchain, artificial intelligence, and edtech. The bottom line seems to be that China is investing in a big way to ensure it remains on the cutting edge when it comes to the technology of tomorrow, whether it's investing billions into AI or leveraging the country's most important social media platform to embrace blockchain. Here are the some of the most interesting tech stories out of China you might not have heard about. Everyone is adopting blockchain technologies, but it's hard for big companies to move at the speed of technological innovation. This is not the case for Tencent in China, makers of WeChat, a social media messaging app with 1 billion active users.

Hoy traemos a este espacio a Make Music and Art Using Machine Learning, que nos presentan así; About Magenta Magenta is a Google Brain project to ask and answer the questions, "Can we use machine learning to create compelling art and music? Our work is done in TensorFlow, and we regularly release our models and tools in open source. These are accompanied by demos, tutorial blog postings and technical papers. To follow our progress, watch our GitHub and join our discussion group. It's first a research project to advance the state-of-the art in music, video, image and text generation. So much has been done with machine learning to understand content--for example speech recognition and translation; in this project we explore content generation and creativity. Second, Magenta is building a community of artists, coders, and machine learning researchers. To facilitate that, the core Magenta team is building open-source infrastructure around TensorFlow for making art and music. This already includes tools for working with data formats like MIDI, and is expanding to platforms that help artists connect with machine learning models Douglas Eck Education Innovation Human-Computer Interaction and Visualization Information Retrieval and the Web Machine Intelligence Natural Language Processing Co-Authors I'm a research scientist working on Magenta, an effort to generate music, video, images and text using machine intelligence. Magenta is part of the Google Brain team and is using TensorFlow (www.tensorflow.org), The question Magenta asks is, "Can machines make music and art?

Amazon's Alexa is now your personal butler at the Wynn hotel in Las Vegas. Self-learning software developed by Google defeated the world's best player of the highly complex Chinese strategy game Go. IBM's Watson saved the life of a woman in Japan by correctly diagnosing her with a rare form of cancer that doctors missed. We are rapidly approaching an inflection point in human history where artificial intelligence will exceed human intelligence, and debates about humans vs. machines have become part of our common vernacular. How can we prepare our next generation of students to compete?

In recent months, Microsoft, Google, Apple, Facebook, and other entities have declared that we no longer live in a mobile-first world. Instead, it's an artificial intelligence-first world where digital assistants and other services will be your primary source of information and getting tasks done. Your typical smartphone or PC are now your secondary go-getters. Backing this new frontier are two terms you'll likely hear often: machine learning and deep learning. These are two methods in "teaching" artificial intelligence to perform tasks, but their uses goes way beyond creating smart assistants.

Two new training provider partnerships are exploring the possibility of using artificial intelligence (AI) to help. Last month, Mandel Communications announced a partnership with Orai on a free communication coaching app that uses AI to provide instant feedback on speech, including clarity, the use of filler words, pacing and energy. This feedback is based on computational linguistics research and a data set of, according to co-founder Danish Dhamani, "thousands of people with different accents, different languages … speaking across the world." The app also includes Mandel's communication skills training and the ability to send recordings to users' managers and coaches for continued development. The company also offers the ability to create custom content for a company's specific messaging.

Americans don't fear artificial intelligence as much as is commonly believed, a new study by Gallup and Northeastern University has found. Officials at Northeastern say that it shows higher education should be more involved in training people for the artificial intelligence world. In a survey of 3,297 adults, about three-quarters said artificial intelligence has and will continue to have a fundamental, but also positive, effect on their lives. Among blue-collar workers, that number dipped to 68 percent. But nearly three-quarters of participants (and 82 percent of blue-collar workers) admitted the revolution will take more jobs than it creates.

When David Stinson finished high school, in Grand Rapids, Michigan, in 1977, the first thing he did was get a job building houses. After a few years, though, the business slowed. Stinson was then twenty-four, with two children to support. As he explained over lunch recently, that meant finding a job at one of the two companies in the area that offered secure, blue-collar work. "Either I'll be working at General Motors or I'll be working at Steelcase by the end of the year," he vowed in 1984.

Temple University's Fox School of Business will launch a new, artificial intelligence (AI) feedback tool to help MBA students better prepare for job interviews this Spring. In partnership with Quantified Communications--a big data and behavioral analytics firm--Fox's feedback tool will combine proprietary analytics with insight from experts to provide each student with personalized feedback on their verbal and oral fluency, two key factors that influence interview performance. Fox joins an elite roster of business schools offering the new technology, including Harvard Business School and The University of Texas at Austin's Executive MBA program. "MBA candidate recruiting is changing; employers are turning to AI to improve the hiring process and the AI market is expected to grow to some 47 billion by 2020," says Janis Moore Campbell, director of graduate professional development at Fox for the past six years. "It's something we can't ignore at Fox. We're striving to stay on top of the most effective ways to help our students fare well."

Why do we need Machine Learning? Machine learning is needed for tasks that are too complex for humans to code directly. Some tasks are so complex that it is impractical, if not impossible, for humans to work out all of the nuances and code for them explicitly. So instead, we provide a large amount of data to a machine learning algorithm and let the algorithm work it out by exploring that data and searching for a model that will achieve what the programmers have set it out to achieve. Let's look at these 2 examples: Then comes the Machine Learning Approach: Instead of writing a program by hand for each specific task, we collect lots of examples that specify the correct output for a given input. A machine learning algorithm then takes these examples and produces a program that does the job.