In this one-hour webinar followed by live Q&A, you will learn about the STM32Cube function packs that allow you to run AI computer vision applications on STM32 microcontrollers, such as the FP-AI-VISION1. We will showcase several examples of computer vision applications based on Convolutional Neural Networks, including people-counting and facial recognition demos, and present the roadmap for edge AI computer vision on STM32 MCUs. After the webinar, there will be a 15-minute Q&A session where our experts will be available to answer any questions. This webinar will be broadcast twice, at convenient times for international audiences. Please review the times listed below and register for the most appropriate option for your time zone.

Welcome to this tutorial on building a deep learning model for malware classification. As we all know, malware detection is one of the most challenging task for IT companies. A huge effort is made by antivirus vendors to always update their solution in order to thwart new types of computer viruses. On the other hand, malware signature is constantly modified in order to bypass antivirus. The good news here is that great deal of new malware versions are slight modifications of older ones . In other words, the binary of new malware versions differs very slightly from those of versions that are already managed by antiviruses.

Ensemble learning refers to machine learning models that combine the predictions from two or more models. Ensembles are an advanced approach to machine learning that are often used when the capability and skill of the predictions are more important than using a simple and understandable model. As such, they are often used by top and winning participants in machine learning competitions like the One Million Dollar Netflix Prize and Kaggle Competitions. Modern machine learning libraries like scikit-learn Python provide a suite of advanced ensemble learning methods that are easy to configure and use correctly without data leakage, a common concern when using ensemble algorithms. In this crash course, you will discover how you can get started and confidently bring ensemble learning algorithms to your predictive modeling project with Python in seven days. This is a big and important post.

Electrification was, without a doubt, the greatest engineering marvel of the 20th century. The electric motor was invented way back in 1821, and the electrical circuit was mathematically analyzed in 1827. But factory electrification, household electrification, and railway electrification all started slowly several decades later. The field of AI was formally founded in 1956. But it's only now--more than six decades later--that AI is expected to revolutionize the way humanity will live and work in the coming decades.

Deep Learning: Advanced NLP and RNNs Over the past year, many of you have been asking for a followup on my RNN and Deep NLP courses. I am glad to announce that today, that course is here. Highest Rated What you'll learn It's hard to believe it's been been over a year since I released my first course on Deep Learning with NLP (natural language processing). A lot of cool stuff has happened since then, and I've been deep in the trenches learning, researching, and accumulating the best and most useful ideas to bring them back to you. So what is this course all about, and how have things changed since then?

Description NumPy is a leading scientific computing library in Python. Whether you are trying to go into Data Science, dive into machine learning, or deep learning, NumPy is one of the top Modules in Python you should understand to make the journey smooth for you. In this course, we are going to start from the basics of Python NumPy to the advanced NumPy. This course will give you a solid understanding of NumPy and its functions. At the end of the course, you should be able to write complex arrays for real-life projects.

Video is the world's most popular content medium, and is shared 1200% more on social media than any other type of content. YouTube reports that mobile video consumption is rising at least 100%, every year, and by 2021, it's estimated nearly 80% of ALL content shared will be video. We're passionate about the power of video, and because we know this is such an important content medium, that's only going to become even more critical to your marketing success in the future, we wanted to combine our shared knowledge to bring you this comprehensive course. Having video content increases your chance of gaining a front-page Google result by 53 times, and including video on a landing page can increase your conversions by 80%! Knowing how to create video with impact, is an essential skill to possess if you want to maximise your marketing in today's competitive, visually orientated climate. Not only this, but as most people don't know how to shoot and market video content the right way, if you do, you'll have the edge on ALL your competitors.

When the constitution of the American Association for the Advancement of Science was revised in 1946, its statement of objectives contained new language: “…to increase public understanding and appreciation of the importance and promise of the methods of science in human progress.” The association has since fulfilled that charge in diverse sectors, including policy, education, and public engagement, to make science more relatable and relevant to the public. Making science relatable also requires a variety of engagement strategies, including facilitating in-depth discussions with local policy leaders, translating technical language into digestible summaries for the classroom, and promoting science role models. In the case of the AAAS Center for Scientific Evidence in Public Issues or EPI Center, for instance, a successful part of bringing clear and actionable scientific advice to policy-makers has been encouraging discussions among a broad group of experts and policy peers. During meetings organized by the EPI Center this year, city council members, mayors, water engineers, and local utility managers joined scientists to discuss perand polyfluoroalkyl substances or PFAS, synthetic chemicals found in drinking water systems. At least two PFAS have been associated with increased rates of some cancers and thyroid disease. The EPI Center provides nontechnical syntheses of topics for policy-makers, “but one thing we have seen is that examples from their peers that have implemented and used the scientific evidence are much more valuable and easier to understand,” said Kathryn McGrath, communications director for the center. Whether the focus is clean water or voting technology or hydraulic fracturing, the EPI Center strives to make the science of these topics relatable by talking with the public and policy-makers to find out exactly what information would be helpful for them. The discussions allow city council members, for instance, “to ask the science experts what they need to know to go back to their communities and regions and take action on some of these issues,” McGrath said. AAAS's Local Science Engagement Network, a grassroots platform that nurtures local and state science advocates for climate and energy policy, has also found success with local partnerships. In Colorado, Missouri, and Georgia, LSENs work with organizations in each state that “have a good sense of policy landscapes as well as the cultural and scientific landscapes in those areas,” said Daniel Barry, local and state advocacy director and head of LSEN at AAAS. LSENs offer an avenue for engagement and advocacy that AAAS members have been asking for, by connecting scientists with their own elected representatives on the local, state, and federal levels. As both constituents and neutral, honest brokers of scientific information, LSEN participants can be a key resource when legislatures grapple with the more local implications of climate change, such as modernizing the state power grid, said Barry. “They can step up and say, ‘Science, that's what I do, and I live here in this community. I know how to get you the science you need.’” LSEN members also condense technical research into locally relevant analyses in plain English for business leaders and citizens. So far in 2021, Missouri LSEN partner MOST Policy Initiative has produced more than 80 such “science notes” about pending state legislation. Among AAAS's numerous education efforts to make science more relevant is Science in the Classroom, an initiative that annotates and provides additional resources to accompany research papers from the Science family of journals. The goal is to make scientific papers more accessible to high school, community college, and undergraduate students, while putting a face on the papers' authors in communities with little exposure to working scientists, said program director Suzanne Thurston. The popular resource had more than 1 million page views in the past 3 years, and the hunger for accessible scientific content during a pandemic year led to a 50% increase in total site visits in 2020 compared to 2019. The program also offers professional development workshops to educators, researchers, and annotators. By showcasing a range of authors and annotators, Science in the Classroom helps “to expose students to diversity within STEM and demonstrates what ‘actual living scientists’ look like,” said Thurston, who serves as a program director in AAAS's Inclusive STEM Ecosystems for Equity and Diversity (ISEED). The IF/THEN Ambassador program, led by AAAS's Center for Public Engagement with Science and Technology, was another recent effort to show off the diverse faces of science, by highlighting 125 women in STEM as role models for middle school girls. Lyda Hill Philanthropies, which funds the IF/THEN initiative, wanted to work with AAAS on the ambassador program after the association's success with other public engagement initiatives such as the AAAS Mass Media Science & Engineering Fellowship and the Leshner Leadership Institute for Public Engagement with Science, said Emily Therese Cloyd, director of the AAAS Center for Public Engagement with Science and Technology. The ambassador program was distinguished by its emphasis on increasing visibility for women in STEM who demonstrate how science is involved in everyday careers beyond the traditional lab, said Cloyd. “We're moving beyond scientists who work at an academic institution and thinking about the ways that a video game designer or a fashion designer might be using STEM every day.” AAAS is committed to making science relatable and relevant for everyone from policy-makers to educators to students. It is at the core of the organization's mission and will continue to be a top priority for years to come.

Udacity, an online learning platform powering the careers of the future, has announced the creation of the AWS Machine Learning Scholarship Program in conjunction with Amazon Web Services (AWS). The goal for this program is to remove barriers to skills training in machine learning and to cultivate the next generation of Machine Learning (ML) leaders from underrepresented backgrounds, including Women, Black, Latinx, Indigenous and People of Color. Enrollment in the free AWS Machine Learning Foundations course begins today. "AWS strives to help level the playing field for women and people of color, who have been underrepresented in the tech industry for far too long. We are thrilled to collaborate with Udacity to make this sort of technical training more widely available and accessible. We look forward to seeing the incredible innovations in machine learning that are sure to come from this initiative," said Ladavia Drane, Global Head, Inclusion, Diversity and Equity, AWS.