Correlation Based Real-Time Data Analysis of Graduate Students Behaviour

Patil, Shankar M.; Malik, A K

doi:10.1007/978-981-13-9187-3_62

Cited by 10 publications

(5 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Patil S.M., Malik A.K. [6] It has become essential to establish methods for resource use in order to make informed judgements due to the quest for improved performance and reliability.…”

Section: Literature Surveymentioning

confidence: 99%

Novel Approach with Deep Learning Models For Melanoma Skin Cancer Detection

Patil,

Gawade,

Chavan

et al. 2024

AJCT

View full text Add to dashboard Cite

Artificial intelligence methodologies with deep learning models proved very effective in many areas. This research focuses on using deep learning models for the detection of skin cancer melanoma in patients at an early stage. The growth of a malignant melanocytic tumor is the primary cause of melanoma, a deadly form of skin cancer. The most dangerous type of cancer, known as melanoma, is brought on by melanocytes, which produce pigment. Seventy-five percent of skin cancer fatalities are caused by melanoma. Only 15% of patients who have survived over the previous five years, according to a review of the survival rate, have received chronic treatment. The manual system is the issue. The mole has a maximum of six colors, thus the image is troublesome since it has a variety of tints and is hard for humans to distinguish. As a result, we created a model utilizing flask and a pre-trained deeplearning model to handle this issue. The suggested model is optimized using the SGD, RMSprop, Adam, Agagrad, Adadelta, and Nadam optimizers. According to testing, the suggested CNN model with the Adam optimizer performs the best at categorizing the dataset of skin cancer lesions. Also it gives the result specifically to the seven types of the skin cancer with their possible chances in percentage. It achieved a training accuracy of 99.73 % and a testing accuracy of 96.53, which is better than the previous results. In order to lower the mortality rate, this research intends to identify an early treatment for people with skin cancer.

show abstract

“…Patil S.M., Malik A.K. [6] It has become essential to establish methods for resource use in order to make informed judgements due to the quest for improved performance and reliability.…”

Section: Literature Surveymentioning

confidence: 99%

Novel Approach with Deep Learning Models For Melanoma Skin Cancer Detection

Patil,

Gawade,

Chavan

et al. 2024

AJCT

View full text Add to dashboard Cite

show abstract

“…Social media information is enormously unstructured -majority of them are informal conversation with typos, slangs and horrific-grammar. Quest for accelerated performance and reliability has made it imperative to develop strategies for usage of resources to make knowledgeable selections [18]. To attain better insights, it's far vital to clean the records earlier than it can be used for predictive modelling.…”

Section: Pre-processing Datamentioning

confidence: 99%

“…: Entitling, Entitled -> Entitle. Observe: some search engines deal with phrases with the same stem as synonyms [18].…”

Section: D) Stemmingmentioning

confidence: 99%

Fake News Detection using Machine Learning: A Comprehensive Analysis

Kushwaha¹,

Singh²

2022

J. Manage. Serv. Sci.

View full text Add to dashboard Cite

Fake news today is an important fact or the life of social media and in the political world. False news discovery is an important study that should be done for its discovery but there are some challenges as well. Some challenges may be due to the small number of similar resources available collection of data and publications. We suggest in this paper, the discovery of false information using machine learning techniques. We compare three different stages of machine learning strategies. Not only that, but we will be working with three different models namely Logistic Regression, Decision Tree Classifier, and Random Forest Classification. According to the discovery of our project, we have gained your various accuracy each way in sequence. Our project can greatly benefit from finding out if the given information is true or fake.

show abstract

“…For Other Models the accuracy goes on decreasing as the number of words go on increasing as given by user as input to the system.But in our system the random dataset [11] and the NLTK [12] tool with latest version helps in giving the perfect output without considering the number of words in the news and also pickling and unplicking methods boost the predicting the output with perfect accuracy.…”

Section: Va Accuracy Comparison Of Different Models For Fake News Detection Fig 2 Accuracy Of Different Modelsmentioning

confidence: 99%

Detection of Fake News using Machine Learning

More¹,

Jadhav²,

Yadav³

2021

International Journal of Advanced Research in Computer and Comm

View full text Add to dashboard Cite

Information is very important today,every time we read a piece of information or watch news on TV,we look for reliable source.Nowadays fake news is making various issues from harsh articles to made news and planning government proclamations in specific outlets.Fake news and nonattendance of trust in the media are creating issues with enormous ramifications in our overall public.Obviously,a deliberately deceptive story is "fake news" yet recently babbling online media talk is changing its definition [1].Some of them currently utilize the term to excuse the realities counter to their favored perspectives.In this today's era we try to get an information or news from the internet and from the social media handles or YouTube,but Information quality in social media is an increasingly important issue.There are so many fake news or tampered video news spread all over the internet and social media.A large portion of the fake news identification frameworks use the semantic element of the news. Nonetheless,they experience issues in detecting profoundly equivocal fraudulent news which can be recognized solely after distinguishing its importance and most recent related data. Therefore,identifying whether the news in text as well as in video format is fake or real has become an important aspect.So,we intended to solve this problem by using different techniques and algorithms.We will be proposing a system where it will be very easy to identify whether the given NEWS on Social Media is Real or Fake,this NEWS can be in Text form [2].

show abstract

Correlation Based Real-Time Data Analysis of Graduate Students Behaviour

Cited by 10 publications

References 8 publications

Novel Approach with Deep Learning Models For Melanoma Skin Cancer Detection

Novel Approach with Deep Learning Models For Melanoma Skin Cancer Detection

Fake News Detection using Machine Learning: A Comprehensive Analysis

Detection of Fake News using Machine Learning

Contact Info

Product

Resources

About