Saturday, 24 November 2018

What are Chatbots and how does a chatbots work..?? || techtalksgroup ||


A chatbot is an artificial intelligence (AI) software that can simulate a conversation (or a chat) with a user in natural language through messaging applications, websites, mobile apps or through the telephone.

 A chatbot is often described as one of the most advanced and promising expressions of interaction between humans and machines. However, from a technological point of view, a chatbot only represents the natural evolution of a Question Answering system leveraging Natural Language Processing (NLP).



The ability to identify the user’s intent and extract data and relevant entities contained in the user’s request is the first condition and the most relevant step at the core of a chatbot: If you are not able to correctly understand the user’s request, you won’t be able to provide the correct answer.
Returning the response: once the user’s intent has been identified, the chatbot must provide the most appropriate response for the user’s request. The answer may be:

• a generic and predefined text
• a text retrieved from a knowledge base that contains different answers
• a contextualized piece of information based on data the user has provided
• data stored in enterprise systems
• the result of an action that the chatbot performed by interacting with one or more backend application
• a disambiguating question that helps the chatbot to correctly understand the user’s request

Why chatbots are important

Chatbot applications streamline interactions between people and services, enhancing customer experience. At the same time, they offer companies new opportunities to improve the customers engagement process and operational efficiency by reducing the typical cost of customer service.

To be successful, a chatbot solution should be able to effectively perform both of these tasks. Human support plays a key role here: Regardless of the kind of approach and the platform, human intervention is crucial in configuring, training and optimizing the chatbot system.
Which chatbot application is right for you?
There are different approaches and tools that you can use to develop a chatbot. Depending on the use case you want to address, some chatbot technologies are more appropriate than others. In order to achieve the desired results, the combination of different AI forms such as natural language processing, machine learning and semantic understanding may be the best option.
In upcoming posts, we will give you an overview of the main chatbot applications so you can evaluate them based on your specific needs and desired goals.

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Wednesday, 7 November 2018

Top Programming Languages that can be used for implementing Image Recognition || techtalksgroup ||


Image recognition is one of the features that is deployed in most modern devices and programs. The feature has a wide range of applications, the most common one being in security systems. It enables devices to recognize the identity of a person or object just by its image. Face recognition is a product of image recognition.

Best Programming Language For Image Recognition

1. Matlab

                                            matlab programming language for image recognition
Matlab is an independent programming language that has its own framework and IDE which come in a more robust workspace. The programming language comes with a broad range of tools that you can use to handle more technical programming tasks with ease. Image recognition and face processing are some of the tasks that can be handled by Matlab.
Matlab offers an array of built-in tools for matrix calculation. It is imperative to note that image recognition and matrix calculation go hand in hand. Some of the tools that are available in Matlab can perform complex image processing tasks such as cropping, rotating, masking among others.
There is also a dedicated Matlab code for invoking and implementing face recognition feature. This code uses the AT&T database. For this reason, you should download the AT&T database before using this code. Most advanced face recognition applications are written in Matlab.

2.Python

                                            python programming languages for image recognition
Currently, Python is rated as the most popular programming language. Its simplicity and versatility are some of the reasons why many programmers prefer to use it. Despite being simple, Python is a language that you can depend on to perform complex tasks. It can be used to create image processing and recognition features.
The popularity of Python has made it be quite resourceful. It is packed with several libraries that are needed for several functionalities, among them-image recognition. One of the most powerful and efficient libraries is the Scikit-Learn Machine Learning library. Apart from image recognition, the libraries can be used for more intelligent functions such as face recognition and motion detection.

2. C/C++/C#

                                                             c++
You can never go wrong when it comes to the C family of programming languages. They are powerful and can do anything, including creating image processing and recognition functionalities. The C family of programming languages gives you two options for creating image processing feature. You can choose to code everything from scratch whereby you write the codes manually. The second option is to use the existing libraries that are specially designed for these programming languages. These libraries include OpenGLEmguCV, OpenCV, and many others. They have an intelligent image processing feature for image recognition.

4. Java

                                                      Java Programming Language
Like C and C++, we can never afford to underestimate the power of Java programming language. This language is powerful enough to perform complex functionalities. It can be used to create applications for image processing and image recognition.
As a standalone programming language, you can create an image processing functionality from scratch. The advantage of this method is you will have the full control of the functionality. Alternatively, there are powerful libraries that can be incorporated into Java for the purpose of creating the image recognition feature. OpenCV is just one of the libraries that is compatible with Java. You can choose whichever method that suits you.

The OpenCV Tool

                                                               opencv
Open Source Computer Vision is an advanced tool that is used for real-time processing. It is also a cross-platform tool hence can be integrated into any programming language for the purpose of executing image processing and recognition functions. It can be integrated with C, C++, Java, Python and Android programming languages.
OpenCV comes with patent-free algorithms that you can use without any legal restrictions. It can be used for commercial and academic purposes. It has a dedicated Face Recognizer class which you can use to experiment the capabilities of image recognition feature without any hassle. The class is accompanied by an information-rich documentation which will show you how to implement the image recognition feature. In overall, OpenCV is a go-to tool for image recognition regardless of the programming language that you are using.
There are several other programming languages that you can use for developing image recognition functionality. Before you start using any language, learn how to process matrix as it is the building block of image recognition programming.

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