{"id":10163,"date":"2021-03-02T16:07:35","date_gmt":"2021-03-02T10:37:35","guid":{"rendered":"http:\/\/ivyproschool.com\/blog\/?p=10163"},"modified":"2024-11-18T17:39:53","modified_gmt":"2024-11-18T12:09:53","slug":"weekly-data-science-news","status":"publish","type":"post","link":"https:\/\/ivyproschool.com\/blog\/weekly-data-science-news\/","title":{"rendered":"Weekly Data Science News"},"content":{"rendered":"

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Welcome to our weekly data science news<\/span> section where we discuss news, developments, and research about data science, analytics artificial intelligence & machine learning that has happened in the past week. \u00a0<\/span><\/div>\n
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Global Data Science Career Opportunities<\/a><\/span><\/h2>\n<\/div>\n
Data science is a multidisciplinary field that has its roots in statistics, computer science, and data analytics skills. It not only provides a versatile career but also helps in creating global job opportunities. In addition to that, it helps businesses to make data-driven decisions.<\/span><\/div>\n
Companies from all domains, Finance, Marketing, Retail, and Banks have a great demand for data scientists. Data Scientists not only have a good depth of knowledge based on the analysis of data but also have a deeper understanding of both structured and unstructured data. The five biggest tech companies – Google, Amazon, Apple, Microsoft, and Facebook are looking for Data Scientists at a larger level. According to a report shared by the U.S. Bureau of Labor Statistics, “data science expertise will drive a 27.9 percent rise in employment in the field by 2026”. Today, not only there is a huge demand, but there is also a noticeable shortage of qualified data scientists.\u00a0<\/span><\/div>\n
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“If you are passionate about computers and research through data analytics, then pursuing an advanced level data science program is the next step for you”, said Amit Gupta, Director, Narayana Business School.<\/span> “Data<\/span> science is used by experts for collecting data via their technology and social science skills. Hence, an expert data scientist is who collects, stores, analyses and manages the data. It helps an organization to make data-driven decisions”, he added.<\/span><\/div>\n
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Revive the map with Machine Learning<\/a><\/span><\/h2>\n<\/div>\n
A research team from Skoltech and FBK<\/span> (Italy)<\/span> presented a methodology to derive 4D building models using historical maps and machine learning. The implemented method relies on the geometric, neighborhood, and categorical attributes to predict building heights. The method is useful for understanding urban phenomena and changes contributing to defining the actual shapes of the cities.\u00a0<\/span><\/div>\n
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In 3D\/4D city modeling applications based on historical data. The lack of building heights is a major obstacle for accurate space representation, analysis, visualization, or simulations.<\/span> “The<\/span> implemented learning and predictive procedures tested on historical data have proven to be effective and promising for many other applications. Based on a few attributes for the prediction, it expands to diverse real-life contexts with missing elevation data. The resulting models will be a great help in bridging the geospatial knowledge gap in past or remote situations,” Emre Ozdemir, a Skoltech and FBK Trento Ph.D. student, explains.<\/span><\/div>\n
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Machine learning speeding up patent classifications<\/a><\/span><\/h2>\n<\/div>\n
Machine learning is helping the U.S. Patent and Trademark Office shorten the time it takes to assign patent applications to examiners. For instance, it is helping them as they do not have to redo its entire classification process, according to CIO Jamie Holcombe. USPTO sent its top engineers to Google on the East and West coasts to learn more about ML and TensorFlow application programming interfaces. Now those engineers are using Python with TensorFlow to apply ML to patent classification, search, and quality.<\/span><\/div>\n
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\u201cWe immersed them in the culture, and they got Googly,\u201d Holcombe said during an ACT-IAC event Wednesday.<\/span> \u201cThey<\/span> got certified in TensorFlow, which is the open-source library for a lot of neural network feedback loops.\u201d USPTO has patent examiners use those feedback loops to rate how well ML algorithms are classifying patent applications to the art units and examiners that evaluate them, as well as search for algorithms in the system. Despite having 250 years of historical data to train its algorithms with, USPTO relies primarily on daily feedback from examiners to ensure they\u2019re working. USPTO remains in the early stages of ML use, in part because it\u2019s still cleaning its data. While the agency uses robotic process automation<\/span> (RPA)<\/span> for clerical and administrative processes, it\u2019s still getting used to the technology before applying it to patent and trademark workflows, Holcombe said.<\/span><\/div>\n
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A deep learning technique: solve Rubik’s cube<\/a><\/span><\/h2>\n<\/div>\n
Colin G. Johnson, an associate professor at the University of Nottingham, recently developed a deep-learning technique that can learn a so-called<\/span> “fitness<\/span> function” from a set of sample solutions to a problem. It was initially trained to solve the Rubik’s cube, the popular 3-D combination puzzle invented by Hungarian sculptor Ern\u0151 Rubik.<\/span><\/div>\n
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The technique devised by Johnson is based on two main approaches. One is stepwise learning and the other is the use of a deep neural network. When applied to Rubik’s cube, the technique tries to unscramble it step by step. In other words, it tries to shift its parts to achieve a simpler configuration, repeating this step several times, until it solves the cube.<\/span><\/div>\n
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Johnson evaluated the technique he developed in a series of experiments. In addition to that, he compares it with a previously developed approach based on a class of algorithms called random forest classifiers, with a baseline approach. It was not only based on traditional error-based fitness but also on other existing computational techniques. His deep learning technique compared favorably with all these alternative methods, while also highlighting the advantages of tackling tasks in a step-by-step way.<\/span><\/div>\n
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Cloudera launches Applied ML Prototypes<\/a><\/span><\/h2>\n<\/div>\n
Cloudera has launched Applied ML Prototypes. In addition to that, it is a complete machine learning project for use cases that give data scientists a running start on development. <\/span>The AI and ML deployments are well underway. For CXOs the biggest issue will be managing these initiatives and figuring out where the data science team fits in. In addition to that, it will be also about what algorithms to buy versus build.<\/span>\u00a0<\/span><\/div>\n
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Cloudera plans on adding dozens of AMP use cases that will accelerate the use of emerging machine learning. <\/span>Santiago Giraldo, director of product marketing, data engineering, and machine learning at Cloudera, said AMPs goal is to change how machine learning is delivered going forward. <\/span>\u201cMachine learning remains difficult to get to production. It takes some time to develop the models,” said Giraldo. <\/span>Giraldo noted that AMPs don’t replace what data scientists do but give them a starting-off point so they can focus on the code, nuances, and iterating for the business use case.\u00a0<\/span><\/div>\n

Learn and grow with Ivy<\/h2>\n
Ivy Professional School will continue to bring the latest to its learners through a weekly data science news blog.\u00a0 The growth in data science is huge and 2021 is becoming the turning point of the 21st century. The current requirement and demands outnumber the talent available in Data Science. Join our prestigious diploma<\/a> certificate program backed by NASSCOM, Government of India to propel your career. Have trouble deciding take a look at all our courses<\/a> and reach out to us here<\/a>. We always strive to provide the best learning experience to our learners. Listen to our students<\/a>.<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Welcome to our weekly data science news section where we discuss news, developments, and research about data science, analytics artificial intelligence & machine learning that has happened in the past week. \u00a0 Global Data Science Career Opportunities Data science is a multidisciplinary field that has its roots in statistics, computer science, and data analytics skills. It not only provides a versatile career but also helps in creating global job opportunities. In addition to that, it helps businesses to make data-driven decisions. Companies from all domains, Finance, Marketing, Retail, and Banks have a great demand for data scientists. Data Scientists not only have a good depth of knowledge based on the analysis of data but also have a deeper understanding of both structured and unstructured data. The five biggest tech companies – Google, Amazon, Apple, Microsoft, and Facebook are looking for Data Scientists at a larger level. According to a report shared by the U.S. Bureau of Labor Statistics, “data science expertise will drive a 27.9 percent rise in employment in the field by 2026”. Today, not only there is a huge demand, but there is also a noticeable shortage of qualified data scientists.\u00a0 “If you are passionate about computers and […]<\/p>\n","protected":false},"author":2,"featured_media":10173,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[851,881,552],"tags":[22,467,111,511,110,209],"class_list":["post-10163","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-business-analytics","category-data-science","category-technology","tag-analytics","tag-data-science","tag-ivy","tag-ivy-professional-school","tag-ivyproschool","tag-news"],"yoast_head":"\nData Science Weekly News | Official Blog | Ivy Pro Blogs<\/title>\n<meta name=\"description\" content=\"Follow the latest news in Data Science, Analytics, AI & ML about the Global Data Science Career Opportunities, ML in patent classifications etc. Read More.\" \/>\n<meta name=\"robots\" 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