Research & Review: Machine Learning and Cloud Computing

Journal Information
Total articles ≅ 9

Articles in this journal

Munesh Meena, Ruchi Sehrawat
Published: 13 September 2022
Machine Learning (ML) is a technology that can revolutionize the world. It is a technology based on AI (Artificial Intelligence) and can predict the outcomes using the previous algorithms without programming it. For our project, we will take the help of NLP (Natural Language Processing) which will help us to perceive and sort fake/spam comments. Also, we will be using this tool to prevent fake promotion and help people when buying products on E-commerce sites and as well as to avoid fake comments on Social Media Platforms that spread hate among people. This application will create a transparent and safe internet for everyone. Spam-Attack will be using NLP to achieve the goal and create a better ecosystem for browsing the internet.
Sharan Shetty, Sarala Mary
The phrase "cloud computing" refers to any activities connected with the delivery of hosted services through the Internet. The term "cloud computing" is frequently used to describe data centers that are accessible to many people online. Drops for efficient and secure data dissemination and duplication in the cloud. Technology called Cloud Drop is about cloud data protection, e.g., users have concerns about security when extracting their external sources data on external administrative management. Loss of data can be caused by attacks on other users and nodes in the cloud. Cloud Drops is a ubiquitous awareness platform that closely integrates visual information from Webs have entered the visual contexts that we live in and work. Cloud Drops has a variety of interactive features, including stamp-like advertisements that each displays a small amount of digital data. Numerous screens and their little size enable the user to use the flexible tool, rearrange it reset their information status. We show different forms of forms on stamped screens, bring up the idea of ​​the device and the original use. We suggest light strategies and consultation familiar with small phone form. We to provide ways for tying these parts to the information the user wants to maintain, such as contacts, locations, and websites. To show platform functionality, we present a specific program example. User research provides initial information on the usage of cloud removal by users to give a customized one-information environment advertisements stored throughout the site location of buildings.
Aman Kumar, Flavia D Gonsalves
Conventional fire detection system was based mechanical sensor for fire detection. The smoke particles in the surrounding detected by sensors in the traditional fire detection system. However, this can also lead to false alarms. For example, a person smoking in a room of can activate a general fire alarm system. In addition, these systems are expensive and ineffective if the fire is far away from the detector. An alternatives fire detection system such as system based on computer vision and Image/video Processing technology to manage false alarms from conventional fire detection. One of the most cost-effective ways is to use surveillance cameras to detect fires and alert affected parties. In the following proposed system proposes a technique which will be monitor the outburst of a fire anywhere within the camera range using a surveillance camera. In this Paper, fire alarm system will be developed to efficiently detect fires and protect lives and property from fire hazards. This research describes a fire detection system that uses color and motion models derived from video sequences. The proposed approach identifies color changes and mobility in common areas to identify fires and can therefore be used both in real time and in datasets.
Sahil M. Kargutkar, Omprakash L. Mandge
An impending decision in front is often searched for a past presence for the purpose of gathering information from the data and to make a decision out of it. Machine Learning, a field which allows systems, a computer to be specific to make a fortunate prediction out of past information or experiences. Machine Learning being a phenomenon widely used throughout the technological advances, is constantly finding itself to be introduced to newer domains. Image processing, medical diagnosis, predictions, speech recognition and many more are among the applications of Machine Learning. Digital Marketing, too, emerges for the need and betterment with aid from the field of Machine Learning. Digital Marketing is a way of maintaining relationships with customers for your business through a way of an online medium. Digital Marketing has made the lives of local businesses a lot easier as a target audience can be reached very easily with just a bare touch of technology. Earlier in the days, Traditional Marketing was the only way for the Businesses to promote their products and services which was done by magazines, newspapers, billboards and with the word of mouth, it was capable of doing the bare minimum publicity. Introduction of Digital marketing has paved a way to reach to a wider, broader and the exact specific target audience. Local businesses are flourishing due to the aid of this type of marketing and machine learning plays a huge role in it.
Sanchit Shahi, Rishabh Gautam Shahi, Mahendra Kumar
Today's corporate world focuses not only on the set of skills of the potential employees, but also on their respective personality. Personality helps you succeed in both your professional and personal life. Therefore, recruiters need to be aware of an individual's personality trait. While the number of job seekers is increasing exponentially, the number of positions is declining, making it difficult to manually add the best candidate for the right position to the candidate list by looking at your resume. This article explores a variety of machine learning approaches to efficiently predict the personality by the usage of Natural language processing (NLP) technology. The results showcase that Random-forest achieves higher accuracy than several other algorithms i.e. KNN, SVM and Naive Bayes. This system can be used in many business areas / areas that may require professional candidates. This system reduces the workload of the department (general workers, employment, and training and dismissal department).
P Ancy Grana, Vinod S Agrawal
The technique of determining whether a text is good, negative or neutral is known as sentiment analysis (SA).Sentiment Analysis can be identified by many names like Textual Analysis, Opinion Mining. Sentiment Analysis is a branch of Natural Language Processing (NLP) that focuses on the expression of subjective views and feelings about a topic gathered from multiple sources. Sentiment Analysis is a collection of methods for detecting and extracting opinions and uses them for the benefit of business operation. It is a classification algorithm aimed at finding opinions and decision-making point of view. Sentiment Analysis is performed in many ways, Automatic classification approach involves Nave Bayes (NB), Support Vector Machine (SVM), and Linear Regression is examples of supervised machine learning methods (LR). The data is explored using unsupervised machine learning. Recurrent Neural Network (RNN) derivatives are also used for classification. Rule-based approach involves various NLP process for classification.
Swathi Bhat D, Saritha M, Poojita Reddy Yatakunta, Prathiksha S Naik, Prathima Bhat
Long-term renal damage is a critical issue that has to be addressed using healthcare analytics. It is a kind of kidney disease where the kidney's functionality will be degraded over months or years. Hence, accurate prediction needs to be done so that patients can undergo proper treatment at the right time. The machine learning techniques help to accomplish this. The proposed research will examine the effectiveness of supervised or guided classification algorithms such as Naive Bayesian and K-Nearest Neighbor in predicting the disorders on the basis of accuracy. A web application will be implemented that helps doctors and patients identify the disease and undergo medication with a proper diet plan.
Sharmikha Sree R, Meera S
In today's environment, people are treated as equals to machines. So book lovers didn't have time to read their favorite novels, and even if they did, they couldn't read them manually, couldn't keep track of what they'd read, or remember what they'd read. In addition, not all books are available in the market at the time of need. People are unable to convey their thoughts and ideas on the book. So, using our app, we can keep track of the books we've read and also share our opinions on them. Users can provide comments or feedback on the book, making it easier for other users to choose a book based on the feedback and remarks. All the books published will be available so no need to search in markets for hours. A text reader option will be a feature in it.
Meera S S, Sharmikha Sree R, K. Valarmathi
AI use information mining and computational knowledge calculations to further develop dynamic models. Market Basket Analysis is one of the main affiliation rule learning is an information mining strategy, Consists of examining the much of the time bought thing in the market container of clients. In the existing system is use a Apriority algorithm is used for finding frequent item sets. However, it takes longer to locate frequently used item sets because it must repeatedly scan the database, which is a time-consuming procedure. The proposed method was created to address the shortcomings of the existing approach. The ECLAT algorithm is utilized to separate successive item sets from the data set, and afterward the affiliation rules are made.
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