Challenges and Business Application Cases

A branch of artificial intelligence that allows computers to learn to solve tasks without having been programmed specifically for this purpose, machine learning offers the possibility of developing algorithms to analyze a Canada WhatsApp Number very large number of data. “ Machine learning , or artificial learning in French, is a discipline of research and application which aims at implicit programming, as opposed to traditional programming. Which requires the design of ad hoc computer code. Much of machine learning concerns classes of algorithms capable of inducing representations, patterns, and programs from computer data.“, explains the educational director of the Artificial Intelligence and Big Data (IABD) sector of the ESGI .

The Multiple Challenges of Machine

While artificial intelligence was born in the 1940s-1950s with the beginnings of computer science. The artificial learning models designed today represent statistical techniques that apply to very large amounts of data. “ Machine learning algorithms are essentially based on induction mechanisms, ie identification of representations and rules that generalize disparate information. For example, an algorithm, which learns to distinguish on medical images a benign tumor from a malignant tumor, does not start from any medical theory, but from a simple preliminary labeling of the images. There is thus a whole challenge in articulating human theories, their practices, with digital representations and their impacts.

Automotive Industry

Canada WhatsApp Number
Canada WhatsApp Number

If machine learning makes it possible to exploit the full potential of big data, it is worth going back to the context. In which this massive data, distributed on a very large scale, appeared. “ The idea is in fact not new because, from the end of the Second World War. Scientists understood that the emerging computer science was inseparable from the data flows that it was going to process. Eighty years later, here we are: data and calculations are distributed in vast infrastructure networks. Hardware, software, protocols and languages ​​are evolving to process ever more data, in ever shorter times. The ubiquity of machine learningin our computerized societies raises the question of the possibilities. The limits of these techniques, including their validity in many situations .

With data making it possible to more or less directly link individuals, companies, regardless of their size, and even States. Machine learning constitutes “ a technical fabric intertwined with all the professional, economic and political aspects of human activities. Suffice to say that the stakes are not lacking! Thus, companies or institutions have the ability to analyze and understand what values ​​they can derive from the data they have, how to automate its integration or trade it.


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