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As the Internet’s coverage expands, so does the number of physical items that may connect to it. By 2011, there were roughly 12.5 billion Internet-connected things, and with the arrival of 5G-Internet [3, it is expected to surpass 25 billion by the end of 2020 and 50 billion by the end of 2050 [1].
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A technological stack is made up of all the technical elements needed in the creation of mobile and online applications, including tools, programming languages, frameworks, and technologies.
Projected to witness a soaring growth, Machine Learning is been considered a top Technical Skill according to the employers in the technological arena.
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Programming languages come in various types, each designed with specific characteristics and intended uses. High-level languages, such as Python and Java, offer readability and ease of use by abstracting away low-level details, making them ideal for general-purpose programming. Conversely, low-level languages like Assembly provide more direct control over hardware resources, making them suitable for system-level programming and optimization. Imperative languages, like C and Pascal, focus on specifying step-by-step instructions for computation, while declarative languages, such as SQL and HTML, emphasize what should be achieved rather than how. Procedural languages organize code into procedures or functions, while object-oriented languages, like C++ and Python, organize code around objects and classes, enabling better code organization and reusability.
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. There are several single-semester graduation courses available. Students with non-technical backgrounds can benefit from prior knowledge of analytic tools such as SQL, Tableau, or Excel to jumpstart a data science career.
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Though PHP's prospects may not be as promising as those of other web development languages like Python or JavaScript/jQuery in the coming five years, it will still be used in such contexts. The technology of PHP is constantly in demand by companies.
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CSE Mini Projects for engineering Students gives an outline of your technical knowledge and helps to ensure a future career. Doing it by yourself (DIY) is mandatory in engineering colleges to make you aware of your value in the IT industry.
In the first course of the Machine Learning Specialization, you will: • Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn. • Build and train supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression
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