Mindblown: a blog about philosophy.
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No human intervention needed (automation)
With ML, you don’t need to babysit your project every step of the way. Since it means giving machines the ability to learn, it lets them make predictions and also improve the algorithms on their own. A common example of this is anti-virus softwares; they learn to filter new threats as they are recognized. ML…
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Easily identifies trends and patterns
Machine Learning can review large volumes of data and discover specific trends and patterns that would not be apparent to humans. For instance, for an e-commerce website like Amazon, it serves to understand the browsing behaviors and purchase histories of its users to help cater to the right products, deals, and reminders relevant to them.…
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Software Developer
Often referred to as the creative brains behind computer programs, software developers have the technical skills needed to build programs or oversee the creation by their team. The software they create allows users to perform specific tasks on various devices. This can be anything from playing a game, building a spreadsheet, watching a movie, or creating a new…
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Human-Centered ML Designer
A Human-Centered Machine Learning Designer sounds a lot more complicated to understand than it actually is. To simplify, human-centered machine learning designers are, just that – designers that develop human-like systems that machines can recognize and process. Thus, alleviating the need for humans to manually design programs for every piece of new information. Instead, they help the…
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Data Scientist
Data scientists analyze large amounts of data to make valuable insights on where action can be taken. Not only will a significant portion of time be spent on researching, but you’ll also solve problems, find meaning in the data associated with machine learning, and “understand the deeper implications of and human impact of [the] project”. Data scientists…
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Machine Learning Engineer
Machine Learnin A machine learning engineer is an engineer that uses programming languages such as, Python, Java, Scala, etc., to run experiments with the appropriate machine learning libraries. To describe in more detail, Tomasz Dudek says it well: “… a person called a machine learning engineer asserts that all production tasks are working properly in terms of actual execution and scheduling,…
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Robotics Engineer
The robotics engineer is perhaps one of the first of AI careers, when industrial robots were gaining popularity as early as the 1950s. From the assembly lines to teaching English, robotics has come a long way. Healthcare uses robot-assisted surgeries. Humanoid robots are being built to be personal assistants. A robotics engineer’s job is to…
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Data Analyst
For a long time, the data analyst was someone who collected, cleaned, processed, and analyzed data to glean insights. For the most part, these used to be mundane, repetitive tasks. With the rise of AI, much of the mundane work has been automated. Therefore, the data analyst role has upgraded to join the new set of AI careers.…
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Software Architect
Software architects design and maintain systems, tools, platforms, and technical standards. AI software architects do this for artificial intelligence technology. They create and maintain AI architecture, plan and implement solutions, choose the toolkit, and ensure a smooth data flow. AI-driven companies expect their software architects to have at least a bachelor’s degree in computer science,…
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Software Engineer
AI software engineers build software products for AI applications. They bring together development tasks like writing code, continuous integration, quality control, API management, etc., for AI tasks. They develop and maintain the software that data scientists and architects use. They stay informed and updated about new artificial intelligence technologies. An AI software engineer is expected…
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