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Showing posts from September, 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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Tableau product line

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Let us broadly classify Tableau tools into the following categories:  • Developer tools (Tableau Desktop and Tableau Public)  • Sharing tools (Tableau Server, Tableau Online, Tableau Reader) Developer tools will help you create a visualization and/or dashboards. Sharing tools facilitate the following visualization and/or dashboards tasks:  • Viewing  • Sharing  • Interacting  • Exploring  Tableau Desktop is available in two versions:  • Professional  • Personal  The difference lies in the types of data sources to which one can connect. With Tableau Desktop Professional, one can connect to all the data sources listed on the data connection page  With Tableau Desktop Personal, one can only connect to OData, Microsoft Windows Azure Marketplace DataMarket, and Tableau Data Extract (.tde) files; however, it is possible to save workbooks locally. tableau training   It cannot publish to a Tableau Server (Public or Private). Tableau P
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Location: Austin, TX, USA
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Are You Getting the Most Out of Your General Trends In Data Science?

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                           Data science is a dynamic field; it is constantly changing. Therefore, keeping up with new developments is not just advisable, it is also expected. Otherwise, your know-how is bound to become obsolete sooner or later, making you a less marketable professional. To avoid this, it is important to learn about the newest trends and have strategies in place about remaining relevant in this ever-changing field. General Trends in Data Science Even though data science is a chaotic system and the many changes it experiences over time are next to impossible to predict, there are some general patterns, or trends, that appear to emerge. By learning about the trends of our field, you will be more equipped to prepare yourself and adapt effectively as data science evolves. The Role of AI in the Years to Come Apart from the hype about AI, the fact is that AI has made an entrance in data science, and it is here to stay. This does not mean that everyt
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Location: United States
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Types Of Data Scientists: All the Stats, Facts, and Data You'll Ever Need to Know

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The big data world has a wide variety of problems, causing some natural differentiation in the specific roles that a data scientist may undertake. Also, the profession has not been properly defined yet, so depending on various aspects of one’s background, such as education, the data scientist role can be further differentiated. Based on some research that was done on the topic by a group of scientists. there are four types of data scientists : data developers, data researchers, data creatives, and data businesspeople. Often encountered among the most experienced professionals of the field is a fifth type, a mixed/generic combination of these. While there is a certain overlap among all of these categories (e.g., they are all familiar with data analysis methodologies, big data technology, and the data science process), they are generally quite different from one another in several ways. Let’s examine each one of them in more detail. There are five different types of data scie
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The Tableau Applications Suite

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Introduction and Getting Started with Tableau Tableau was created to empower people to analyze their data regardless of the level of their technical know‐how. At the core of Tableau is VizQL, an innovative visual query language that translates mouse inputs such as drag‐and‐drop into database queries. This allows the user to quickly find insights in their data and to share the results with others. Crucially, it is not necessary to know what you are looking for or how you want to present your findings. Instead, with Tableau, you can immerse yourself in data. Through visual analysis, you will be able to unearth patterns and relationships in your data that you might not have known existed. In this regard, Tableau is different from other tools, which often require you to know beforehand in what form you want to display your data. The purpose of this chapter is to introduce you to the different products that make up the Tableau application suite, the Tableau user interface,
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