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Best Practices for Handling Duplicate Elements in Python Lists

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Here are three awesome ways that you can use to remove duplicates in a list. These are helpful in resolving your data analytics solutions.  01. Using a Set Convert the list into a set , which automatically removes duplicates due to its unique element nature, and then convert the set back to a list. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = list(set(original_list)) 02. Using a Loop Iterate through the original list and append elements to a new list only if they haven't been added before. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = [] for item in original_list:     if item not in unique_list:         unique_list.append(item) 03. Using List Comprehension Create a new list using a list comprehension that includes only the elements not already present in the new list. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = [] [unique_list.append(item) for item in original_list if item not in unique_list] All three methods will result in uni
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Story IoT devices human intelligence basic concepts(1 of 3)

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The definition of Artificial intelligence is the continuous technological advances have gradually surrounded people with a wide range of electronic devices and information technology.
The short name for Artificial intelligence is 'ai'.
In this regard, it is necessary to develop intuitive interfaces and systems with some degree of intelligence, with the ability to recognize and respond to the needs of individuals in a discrete and often invisible way, considering people in the center of the development to create technologically complex and intelligent environments.
artificial intelligence

Artificial Intelligence Vs Ambient Intelligence

  • Artificial Intelligence
  • Ambient Intelligence

1. Artificial Intelligence

  • Artificial intelligence in basic words machines can take decision intelligently
  • They understand natural language - How humans communicate each other
  • Robots - you can treat them as Artificial intelligent machines.
  • Machine Language Algorithms help machines act as intelligent machines.

2. Ambient Intelligence (AmI)

It is an emerging multidisciplinary area based on ubiquitous computing, which influences the design of protocols, communications, systems, devices, etc., proposing new ways of interaction between people and technology, adapting them to the needs of individuals and their environment (Weber, et al. 2005). 

AmI offers a great potential to improve quality of life and simplify the use of technology by offering a wider range of personalized services and providing users with easier and more efficient ways to communicate and interact with other people and systems (Weber, et al., 2005; Corchado, et al., 2008b). 

However, the development of systems that clearly fulfill the needs of AmI is difficult and not always satisfactory. It requires a joint development of models, techniques and technologies based on services.

An AmI-based system consists of a set of human actors and adaptive mechanisms which work together in a distributed way. Those mechanisms provide on demand personalized services and stimulate users through their environment according to specific situation characteristics (Weber, et al., 2005).

AI problems tend to be large. They are computationally complex and cannot be solved by straightforward algorithms. 

AI problems and their domains tend to embody a large amount of human expertise, especially if tackled by strong AI methods. Some types of problems are better solved using AI, whereas others are more suitable for traditional computer science approaches involving simple decision-making or exact computations to produce solutions.

Let us consider a few examples:
  • Medical diagnosis - You can use AI in medical field. Devices that used in Radiology, you can use as an aid to specialist Doctor.
  • Banking Applications- Chatbots are famous AI based tools.

Salary of Artificial Intelligence Engineers

According to Indeed.com, the average IT salary – the keyword is "artificial intelligence engineer" – in the San Francisco area ranges from approximately $134,135 per year for software engineer to $169,930 per year for machine learning engineer.

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