Are you looking for the Best R Programming Certification Online? Here is the handpicked list of Best R Programming Course & Training to assist you to become an expert in programming in R. Before you start doing these courses we have included an article How to Start Programming in R? Go through this article you will get a brief idea about where and how to start learning r? Find out how attractive the r programming jobs are? Description: Learn R will help you gain expertise in R Programming, Data Manipulation, Exploratory Data Analysis, Data Visualization, Data Mining, Regression, Sentiment Analysis and using R Studio for real-life case studies on Retail, Social Media. "R" wins on Statistical Capability, Graphical capability, Cost, a rich set of packages and is the most preferred tool for Data Scientists. Description: Neurohacking describes how to use the R programming language and its associated package to perform manipulation, processing, and analysis of neuroimaging data.
Dozens of scientists funded by Mark Zuckerberg have protested against his decision to leave inflammatory Donald Trump posts on the site. Mr Zuckerberg is allowing the president to use the social network to "spread both misinformation and incendiary statements", the researchers warn. Scientists, including 60 professors at leading US research institutions, wrote to the Facebook boss asking Mr Zuckerberg to "consider stricter policies on misinformation and incendiary language that harms people," especially during the current turmoil over racial injustice. The letter calls the spread of "deliberate misinformation and divisive language" contrary to the researchers' goals of using technology to prevent and eradicate disease, improve childhood education and reform the criminal justice system. Their mission "is antithetical to some of the stances that Facebook has been taking, so we're encouraging them to be more on the side of truth and on the right side of history as we've said in the letter," said Debora Marks of Harvard Medical School, one of three professors who organised it.
Users can perform a function by pressing an Action Block. Google has announced a slew of updates to its suite of accessibility apps to celebrate Global Accessibility Awareness Day. One of the updates is the release of Action Blocks, which allows users to create customisable, home screen buttons for relatively complex actions like playing music or calling somebody that typically require multiple steps -- tasks that may be difficult for people with limited mobility or a cognitive disability. "For people with cognitive disabilities or age-related cognitive conditions, it can be difficult to learn and remember each of these steps. For others, it can be time consuming and cumbersome -- especially if you have limited mobility," Google said.
He is a polymath: a neuroscientist, working on drug-discovery, alcoholism, Parkinson's and basics of time computation in brain. Also a data scientist entrepreneur, an acclaimed visual artist, and a writer, he now runs a neuroscience group at Central Drug Research Institute. Not just this, he has worked in forests with remote tribes and in the most cutting edge drug discovery labs. His works have been juxtaposed with giants of European art, such as Monet, Van Gogh, Degas at the series: The Drifting Canvas. At TEDxJDMC he talked about Artificial Intelligence.
The Engineered-Mind podcast is covering topics related to engineering, artificial intelligence, neuroscience to inspire and educate people all around the world. Experts in their field share their vision and knowledge about AI, AGI & singularity, how the brain works but also psychology, cognitive science and mathematics.
We present a unified statistical framework for characterizing community structure of brain functional networks that captures variation across individuals and evolution over time. Existing methods for community detection focus only on single-subject analysis of dynamic networks; while recent extensions to multiple-subjects analysis are limited to static networks. To overcome these limitations, we propose a multi-subject, Markov-switching stochastic block model (MSS-SBM) to identify state-related changes in brain community organization over a group of individuals. We first formulate a multilayer extension of SBM to describe the time-dependent, multi-subject brain networks. We develop a novel procedure for fitting the multilayer SBM that builds on multislice modularity maximization which can uncover a common community partition of all layers (subjects) simultaneously. By augmenting with a dynamic Markov switching process, our proposed method is able to capture a set of distinct, recurring temporal states with respect to inter-community interactions over subjects and the change points between them. Simulation shows accurate community recovery and tracking of dynamic community regimes over multilayer networks by the MSS-SBM. Application to task fMRI reveals meaningful non-assortative brain community motifs, e.g., core-periphery structure at the group level, that are associated with language comprehension and motor functions suggesting their putative role in complex information integration. Our approach detected dynamic reconfiguration of modular connectivity elicited by varying task demands and identified unique profiles of intra and inter-community connectivity across different task conditions. The proposed multilayer network representation provides a principled way of detecting synchronous, dynamic modularity in brain networks across subjects.
In most real-world applications, it is seldom the case that a given observable evolves independently of its environment. In social networks, users' behavior results from the people they interact with, news in their feed, or trending topics. In natural language, the meaning of phrases emerges from the combination of words. In general medicine, a diagnosis is established on the basis of the interaction of symptoms. Here, we propose a new model, the Interactive Mixed Membership Stochastic Block Model (IMMSBM), which investigates the role of interactions between entities (hashtags, words, memes, etc.) and quantifies their importance within the aforementioned corpora. We find that interactions play an important role in those corpora. In inference tasks, taking them into account leads to average relative changes with respect to non-interactive models of up to 150\% in the probability of an outcome. Furthermore, their role greatly improves the predictive power of the model. Our findings suggest that neglecting interactions when modeling real-world phenomena might lead to incorrect conclusions being drawn.
Technology is Chicago's fastest-growing industry sector, having grown more 270 percent over the last decade, according to World Business Chicago. And 2019 was a model year that not only encapsulated the growth of technology in the city but also positioned Chicago for further success in 2020 and beyond. Influential leaders in tech launched Chicago's Plan for 2033, or P33, to enhance the city's viability as a global tech hub with a strong and diverse workforce through the next decade. Mayor Lori E. Lightfoot said on Chicago Tech Day that 15 local tech companies have added or will be adding 2,000 jobs through 2020. Uber announced it would be bringing that same number of jobs to Chicago over the next three years and spending more than $200 million annually on the city. But it isn't just major initiatives and companies with household names that will be bringing continued success to Chicago tech. Smaller startups entering the city's tech scene are shaping everything from mental health care to cryptocurrency trading to vehicle leasing. We found 50 such companies -- all less than three years old -- that are poised for growth in the coming year. Brett Quillen contributed in writing this report. Interested in Chicago tech?See all open roles on Built In CHI Arturo wants to take property risk management to the skies by using drones and satellite, aerial and ground imagery to assess residential and commercial property characteristics. The data it collects is powered by predictive analytics to give clients that lend, insure or invest in properties the ability to minimize risk and determine market patterns.
Assuming hardware is the major constraint for enabling real-time mobile intelligence, the industry has mainly dedicated their efforts to developing specialized hardware accelerators for machine learning and inference. This article challenges the assumption. By drawing on a recent real-time AI optimization framework CoCoPIE, it maintains that with effective compression-compiler co-design, it is possible to enable real-time artificial intelligence on mainstream end devices without special hardware. CoCoPIE is a software framework that holds numerous records on mobile AI: the first framework that supports all main kinds of DNNs, from CNNs to RNNs, transformer, language models, and so on; the fastest DNN pruning and acceleration framework, up to 180X faster compared with current DNN pruning on other frameworks such as TensorFlow-Lite; making many representative AI applications able to run in real-time on off-the-shelf mobile devices that have been previously regarded possible only with special hardware support; making off-the-shelf mobile devices outperform a number of representative ASIC and FPGA solutions in terms of energy efficiency and/or performance.
This is phase 1 of first lawsuit. We are open for support at a global level. We have a network of thousands around the world and tens of thousands in China, who are witnesses and have been harmed in China from the defendants technology and data transfer.The following are Federal Case Compliant Summary Facts Extracted from the official document filed in San Diego, California. To find out details of financial, personal and corrective behavioral demands, you may access the case in the federal court data base.