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Showing posts from February, 2019

The basic principle of robotics and AI

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Artificial intelligence applied to robotics development requires a different set of skills from you, the robot designer or developer. You may have made robots before. You probably have a quadcopter or a 3D printer. The familiar world of  Proportional Integral Derivative  ( PID ) controllers, sensor loops, and state machines must give way to artificial neural networks, expert systems, genetic algorithms, and searching path planners. We want a robot that does not just react to its environment as a reflex action, but has goals and intent—and can learn and adapt to the environment. We want to solve problems that would be intractable or impossible otherwise. Robotics or a robotics approach to AI—that is, is the focused learning about robotics or learning about AI? about how to apply AI tools to robotics problems, and thus is primarily an AI using robotics as an example. The tools and techniques learned will have applicability even if you don’t do robotics, but just apply AI to
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What is Data Science and Why we Use Data Science?

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Data science may be a multi-disciplinary field that uses scientific ways, processes, algorithms, and systems to extract Data and insights from Data in varied forms, each structured and unstructured, the same as data processing. ... Nate Silver noted Data science as a sexed-up term for statistics. What is the origin of data science? Over the years, Data science has become associate degree integral a part of several trades like agriculture, selling optimization, risk management, fraud detection, selling analytics and public policy among others. By exploitation Data preparation, statistics, prophetic modeling and machine learning, Data science tries to resolve several problems among individual sectors and therefore the economy at the giant. Data science emphasizes the utilization of general ways while not dynamic its application, no matter the domain. This approach is completely different from ancient statistics tend to target providing solutions that square measure spec
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Data science could be a fast-moving field – if you’re following a Data science career, or maybe if you’re simply fascinated by data-related topics, you wish to take a position time to stay up with the trends. Following a couple of high blogs could be a good way to remain au courant developments in  Data analysis, applied mathematics computer code, Data visualization, and more. These 10 bloggers systematically supply nice resources and tutorials, together with opportunities to attach with and learn from alternative leading Data sciences. follow Data Science certification  Simply Statistics Simply Statistics is managed by biostatistics professors Jeff Leek, Roger Peng, and Rafa Irizarry. Regular topics embody knowledgeable opinions and insights into AI and Data usage, and for industrious statisticians, there’s a series of career-focused interviews with  Data scientists regarding their roles among the trade. Flowing  Data  Flowing  Data  offers an intensive library of tuto
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