Applied Sciences

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As is well known, machine learning (ML) is one of the main branches of artificial intelligence (AI). Its primary objective is to use computational methods to extract information from data. Machine learning has a wide spectrum of practical applications. After the first applications concerning topics such as recognition of manual writing, detection of objects in image processing, voice recognition, medical diagnoses, DNA classification, search engines, and stock market analysis, in recent years machine learning algorithms have been increasingly used in environmental sciences due to their high capability for modelling non-linear phenomena. In particular, these algorithms are already widely used in weather and climate forecasts, as well as in the analysis and modelling of hydrological, ecological, and oceanographic data.


Significance of Data Transformation in Machine Learning Analytics Insight

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Machine Learning advancements allow enterprises to process and comprehend their data much faster using modern tools with validated algorithms. But that data can be intricate and chaotic in its raw state. Thus, some form of data transformation here is required before any data analysis that can assist in accomplishing business use cases such as market campaigns, implement efficient logistics operations, outpace competitors, among others. Data transformation makes businesses' data more constructive. However, it can be time-consuming, expensive, and monotonous if the right technology stack not in place.


Google's supremacy from information retrieval

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TITOLO: Google's supremacy from information retrieval, passing through Natural Language Modeling, to quantum computing ABSTRACT: The current era of data is dominated by a few big players. Among them, Google is playing the role of a significant technological innovator. Its story started from Information Retrieval algorithms is evolving in many fields of research, including natural language processing, user modeling, and quantum computers. The talk will discuss some of the algorithms proposed by google as state of the art in the last years for performing innovative tasks in machine learning, NLP, and more from a research point of view applied in everyday tasks. RELATORE: Marco Polignano BIO RELATORE: Marco Polignano is a PostDoc Research Fellow at the Department of Computer Science, University of Bari Aldo Moro, Italy, in the SWAP (Semantic Web Access and Personalization) research group.


Michael Kearns: Algorithmic Fairness, Privacy, and Ethics in Machine Learning AI Podcast

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Michael Kearns is a professor at University of Pennsylvania and a co-author of the new book Ethical Algorithm that is the focus of much of our conversation, including algorithmic fairness, privacy, and ethics in general. But, that is just one of many fields that Michael is a world-class researcher in, some of which we touch on quickly including learning theory or theoretical foundations of machine learning, game theory, algorithmic trading, quantitative finance, computational social science, and more. This conversation is part of the Artificial Intelligence podcast. This episode is sponsored by Pessimists Archive podcast: https://pessimists.co/ OUTLINE: 0:00 - Introduction 2:45 - Influence from literature and journalism 7:39 - Are most people good?




Assisting a finance business to harness the power of AI in advertising and marketing

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The company requested that Faculty determine the major strategic opportunities for it, including optimisation of the existing business functions through the application of new technologies and the creation of new revenue opportunities using AI. We were asked to engage with and execute the most impactful of these opportunities, in collaboration with the company's internal team. First, we identified areas where data was being under-utilised and where AI could add value. Then we made recommendations about the organisational and personnel structure. We provided training for employees in data science management, helped to recruit a new head of data science and filled data scientist roles from Faculty Fellowship programme.


2020 will be the year the issues holding HR back will be resolved with AI playing a big part

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A director has said that investing in Artificial Intelligence (AI) allows those working in HR to focus on where their real value lies like creating workplace cultures that drive recruitment, retention, productivity and performance instead of spending time doing less vital tasks. This is the opinion of Damian Oldham, divisional director at the Access Group a provider of HR software who sees AI as tool professionals in HR can use to make themselves more effective at their job. Mr Oldham believes senior leaders are being urged to use 2020 as the year where they tackle the issues holding HR teams back. He believes HR has reached a "critical point due to data-led systems, capable of automating many transactional tasks quickly and accurately." It would be easy to assume HR professionals are worried about automation threatening their jobs, but nothing could be further from the truth.


Jio Institute to offer undergraduate courses in AI, machine learning and more

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Mukesh Ambani's Jio Institute will start its first academic session in 2021. It will focus on undergraduate courses in emerging technologies like artificial intelligence, data science, machine learning, and digital media and marketing. The digital courses will be led by Shailesh Kumar, who is the chief data scientist for Jio. The Human Resource & Development (HRD) Ministry had granted the'eminence' status to the Jio Institute even before it went operational. Mukesh Ambani's Jio Institute which will start its academic session in 2021 -- will offer courses in emerging technologies like artificial intelligence, data science, machine learning, digital media and marketing.


Internship Opportunities: Computer Vision ai-jobs.net

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Microsoft Research provides a dynamic environment for research careers with a network of world-class research labs led by globally-recognized scientists and engineers. Our researchers and engineers pursue innovation in a range of scientific and technical disciplines to help solve complex challenges in diverse fields, including computing, healthcare, economics, and the environment. It has never been a more exciting time at the Computer Vision Group at Microsoft Cloud & AI! We continue to advance the state of the art in the areas we choose to study. The Computer Vision Group is tasked to improve our odds of betting on the "next big thing" and impact various products in the areas of cloud and edge intelligence, such as Microsoft Cognitive Services and HoloLens.