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In the era of Artificial Intelligence (AI) a machine (computer) performs a specific task with the help of a model. Machine Learning (ML) is the study of these kinds of models and algorithms. Machine Learning Algorithms (MLAs) have proven successful in extracting patterns from images and sensing anomalies to detect fraud. While Machine Learning has solved many problems, there is still a large gap compared to the abilities of human learning. One of the biggest challenges in using ML technology is providing sufficient data to train a model.  Large amounts of data are required for the model to work. Humans learn using an adaption mechanism and are able to discern relationships using a variety of information.  Machine Learning, however, does not have this ability, but instead relies on a large set of data to train the model. For Machine Learning to work it is important to select the appropriate set of features from…

Machine Learning (ML) has emerged as an important technology that is quickly becoming a part of our everyday life. Working with Artificial Intelligence (AI) technology, ML allows software applications to learn from the data and become more accurate in predicting outcomes without human intervention and without being explicitly programmed. To make this happen, programmers use tools and libraries to handle ML tasks. Here is an overview of some of the most common tools used to make this technology work:Scikit Learn is a free software ML library for the Python programming language. It is a simple and efficient tool for data mining and data analysis. It is built on Numpy, Scipy, and Matplotlib platforms and provides a range of supervised and unsupervised learning algorithms in Python such as classification, regression, clustering and more. Scikit Learn is the basic building block for any Machine Learning algorithm.KNIME is a free and open-source data analytics reporting and integration…

Facial Recognition Artificial Intelligence (AI) technology is becoming part of our everyday life and its applications can be seen in areas such as bank fraud detection, retail purchase predictions and online customer support interactions. AI has also proved useful in detecting and stopping malware threats and cyber attacks. An emerging area of AI is Facial Recognition technology – the ability to identify or verify a person from a digital image or video source. Several methods are being used in which facial recognition systems work, but in general, they work by comparing selected facial features from a given image with faces within a database. Iris Recognition Iris recognition is one of the most popular types of biometric technology because of its narrow margin of error and fast speed. It is an automated method of biometric identification and verification that uses mathematical pattern-recognition techniques on images of a person’s eyes.  The iris offers complex, unique…

The central goal of Artificial Intelligence (AI) is to create intelligent and smarter machines. In broader terms, AI refers to multiple fields of study, such as Machine Learning (ML), Robotics, Natural Language Processing (NLP), and Neural Networks. These technologies have transformed AI into a robust tool, that has radicalized the decision making process and promises to change the way we do business.AI and Machine Learning are already impacting several areas of our lives, from the “Hey, Siri” and “OK, Google” interactions that facilitate our ability to find information or navigate our environments, to online recommendation systems that we get from Facebook, Netflix, Amazon, and others.The question that now arises is how these AI and ML technologies will impact organizations and industries – and how will these technologies benefit companies in creating a competitive edge?A key area where AI and ML promises to create value in organizations is the acceleration of the decision making…