Hello, I'm Krishna Mridha

Phishing Website Detection

Basically, this is an interesting application to detect the "Phishing URLs". Sometimes, stranger want to access the credentials of any users. For this reason, they have send so many URL link. This link may be contain abnormalities. So, this application is gonna help to identify those URL. This is the very first stage of this research . It's performance is not good at all. We are trying to increase the performance.

Brest Cancer Classification

Breast Cancer currently affects and destroys most women. This is because breast cancer is the world's second-most deadly cancer. 12% of all current forms of cancer and 25% of all women's cancers are breast cancer. Tumors that can be cancerous are called the being out influence implementation of cells in an organ. Benign and malignant are two types of tumors that are available in the world. 

Admission Prediction

This project predicts the admission of a student based on different features including university rating, student’s undergraduate GPA, GRE score, research experience and etc. This predicts that how many chances are there that the student will get admission to his selected university or not. Normally, students suffering from habitation what they should do. 

Student Performance Prediction

Education is a very important issue regarding the development of a country. The main objective of educational institutions is to provide high-quality education to their students. One way to accomplish this is by predicting a student's academic performance and thereby taking early steps to improve student's performance and teaching quality.

Smart Attendance Management 

We can make our Attendance Management System (AMS) intelligent by using a face-to-face recognition strategy. For that, we have to fix a CCTV camera at the classroom at any best point, which makes a person's picture at the fixed time and tests a face-to-face image. Traditionally, student attendance at the institutes is manually reported on the attendance sheets.

Bank's loan approval

This is a really interesting automated forecasting framework for every bank that offers a loan to customers. The Company wants to automate the credit eligibility process (real-time) based on the customer information given when filling out the online application form. This information includes gender, marital status, education, number of dependents, wages, loan size, credit history, and others.

Salary Prediction

The purpose of this project is to make accurate salary predictions that are based on existing known salaries so the company is able to recruit and retain top talent. This model will help the company offer

Diabetes Prediction

Using a Data analysis technique, one can study a huge dataset and find deeper information, deeper patterns, deeper symptoms from the data, and predict outcome accordingly. The intension of this recitation is to scheme a unique model that can predict diabetes with maximum accuracy. In the existing method, the classification and prediction accuracy is not that high.

Air Flight Price Prediction

Machine Learning is a part of Artificial Intelligence. In Machine Learning, there are many algorithms exist. In this project usually I used Linear Regression to predict the Air Flight Price. Even though we have many apps in line through them we also can check the price but the difference between this app and my model is this price is select or modified by the author of the particular airlines but my model can predict the price without any modifications.

Car Price Prediction

Using a Data analysis technique, one can study a huge dataset and find deeper information, deeper patterns, deeper symptoms from the data, and predict outcome accordingly. The intension of this recitation is to scheme a unique model that can predict diabetes with maximum accuracy. In the existing method, the classification and prediction accuracy is not that high.

Covid-19 data analysis

descriptionMachine Learning is a part of Artificial Intelligence. In Machine Learning, there are many algorithms exist. In this project usually I used Linear Regression to predict the Air Flight Price. Even though we have many apps in line through them we also can check the price but the difference between this app and my model is this price is select or modified by the author of the particular airlines but my model can predict the price without any modifications.

Toward Explainable Cardiovascular Disease Diagnosis: A Machine Learning Approach

Cardiovascular diseases (CVDs) are one of the leading causes of mortality globally. Early and accurate diagnosis is crucial for the effective treatment and management of CVDs. In this study, we propose a machine learning-based approach for CVD diagnosis using the “cardiovascular disease dataset” obtained from Kaggle. The dataset comprises 70,000 records of patient data, including 11 features and a target variable. The features are classified into three types: objective, examination, and subjective. We implemented six machine learning algorithms, and our results showed that logistic regression performed better with an accuracy of 74%.

Implementing an Alarm Based Driver Drowsiness Detection System for Traffic Safety Using Neural Network

Driver drowsiness is a very common issue that can lead to severe accidents on the road. According to studies, drowsy driving is a factor in about 20% of road accidents, with some estimates suggesting that the number could be even higher. The consequences of drowsy driving accidents can be devastating, including loss of life, serious injuries, and significant property damage. Drowsy driving is especially dangerous because it impairs a driver's reaction time, decision-making ability, and overall awareness of their surroundings.

Accuracy and Interpretability: Developing a Computer-Aided Diagnosis System for Pneumonia Detection in Chest X-Ray Images

People of all ages can contract pneumonia, a deadly respiratory illness that is more common in underdeveloped countries. For successful treatment and higher survival rates, pneumonia must be accurately and quickly diagnosed. While chest X-ray imaging is a frequently used diagnostic technique for detecting pneumonia, its interpretation can be arbitrary and error-prone. In this study, we used a convolutional neural network (CNN) architecture to construct a computer-aided diagnostic system for pneumonia identification in chest X-ray images.

Explainable Deep Learning for Coffee Leaf Disease Classification in Smart Agriculture: A Visual Approach

In recent years, the application of deep learning techniques for plant disease classification has become increasingly important for smart agriculture. Early classification and treatment of plant diseases are crucial for maintaining the quality and quantity of crops, and deep learning algorithms have the potential to provide accurate and efficient solutions to this problem. In this study, we used two datasets collected from Mendeley for coffee leaf disease classification. The first dataset contained two classes of images, while the second dataset contained the remaining three types of images. The two datasets were combined to create a more robust dataset for training the two-transfer learning and CNN model.

Deep Learning in Lung and Colon Cancer classifications

The past few decades have seen revolutionary advancements in the field of Healthcare and Medicine. During this period, the underlying reasons for many fatal diseases have been unveiled, novel diagnosis techniques were invented, and medical solutions were developed. Instead of these breakthroughs, we are still vulnerable and haunted by certain diseases like cancer. Globally, cancer is the second most common cause of mortality which accounts for the death of one in every six affected individuals. Among many other types, the colon and lung are the most prevailing and life-threatening ones. Only these two variants are responsible for 25% of all cancer cases around the world. However, early lung and colon cancer detection can significantly enhance the possibility of survival.

Temporal Features and machine Learning Approaches to Study Brain Activity with EEG and ECG

Electroencephalogram (EEG) and Electrocardiogram (ECG) are electrical signals that reflect activities of the brain and cardiac, respectively, based on which some neurological disorders and mental status are determined. In this paper, a novel set of temporal features like energy, Shannon energy, entropy, and temporal energy, all together along with machine learning-based classifiers to identify the relaxing state of humans and while performing mental tasks like arithmetic operations using these signals are proposed.

Estimated of Concrete Compressive Strength by Using Neural Network and Machine Learning

The most fundamental input of the construction sector is concrete, which would be a massively complicated element. Concrete is among the most common structural construction materials due to its strength. Since some manufacturers manufacture out of reach and low quality, there is a growing demand for earthquake-resistant design in the fully prepared concrete industry. Concrete's strength-gaining properties are influenced by a variety of factors. This research aims to use the results of early compressive strength tests to predict strength properties at various ages. The ability to estimate the determination and strength of normal concrete using the early day strength properties result has been examined.

Use of Machine Learning in Predicting Diabetes

Diabetes mellitus, commonly known as diabetes, is a metabolic disease that causes high blood sugar. We all know that the hormone normally passing through the blood to our cells for gathered energy. Any Diabetes contains unprocessed high blood that can damage our nerves, eyes, kidneys, hearts, and other organs. In certain times, there are a lot of people suffer or affected by diabetes for the reason the people have to go to the diagnostic center, hospital, or clinic for tests. So naturally, the management has to store the required tests report and provide a proper diagnosis based on them report. But the rise in machine learning approaches solves this critical problem.

Early Prediction of Breast Cancer by using Artificial Neural Network and Machine Learning Techniques

Acoustic For a limited number of disorders, early diagnosis of any illness may be curable to mankind's commitment. Before it becomes chronic, most persons fail to detect their illness. This adds to a global rise in mortality rates. Breast cancer is one of the cancers that can be treated until it progresses to all areas of the body as the condition is diagnosed at early stages. Breast cancer primarily affects women and it is also an important factor in raising the rate of female mortality. We are both mindful that the diagnosis of breast cancer is very time-consuming.

Study and Analysis of Implementing A Smart Attendance Management System Based on Faced Recognition Technique Using OpenCV and Machine Learning

We can make our Attendance Management System (AMS) intelligent by using a face-to-face recognition strategy. For that, we have to fix a CCTV camera in the classroom at any best point, which makes a person's picture at a fixed time and tests a face-to-face image. Traditionally, student attendance at the institutes is manually reported on the attendance sheets. It's not a productive operation, because it takes 5 or more minutes for attendance. Normally, the length of our class is 50 minutes, and every day we have more than 5 lessons. 

Navigating Modern Science: Insights from Jeff Leek's "How to Be a Modern Scientist"

- Krishna Mridha

Introduction

In an era defined by rapid technological advancements and an overwhelming influx of data, the archetype of a successful scientist has evolved significantly. "How to Be a Modern Scientist" by Jeff Leek offers a roadmap for navigating this new terrain. Through his book, Leek advocates for a blend of traditional scientific rigor and modern data science skills. This blog post delves into key takeaways from the book, emphasizing how they can revolutionize scientific practices.

The Imperative of Data Literacy

Data literacy stands as the cornerstone of modern scientific research. Leek articulates that understanding data isn't merely about statistical calculations; it encompasses data management, interpretation, and clear communication. He insists that a modern scientist must be proficient in software tools that manage and analyze large datasets, apply complex statistical models, and visualize data effectively. This skill set enables scientists to extract meaningful insights from vast amounts of information, a capability that is now indispensable in most scientific inquiries.

Embracing Open Science

Leek's book stresses the significance of open science—an approach that promotes accessibility, transparency, and collaboration in research. Open access to publications, sharing data freely, and using preprints to disseminate findings promptly are practices that enhance the reproducibility of scientific results and accelerate the advancement of knowledge. This shift towards openness is not only about accessibility but also about building a global community of researchers who can contribute to, and benefit from, shared resources.

Ethical Data Management

With the power of data comes great responsibility. Leek dedicates a substantial portion of his book to the ethical dimensions of handling data. Modern scientists must navigate the complexities of data privacy, security, and ethical use. This involves understanding the legal implications of data use, ensuring the confidentiality of sensitive information, and conducting research that adheres to high ethical standards. These practices are crucial for maintaining public trust and integrity in scientific research.

Communication Skills

Leek also emphasizes the importance of effective communication in the life of a modern scientist. This includes not only writing clear, accessible research papers but also engaging with non-scientific audiences through popular media, blogs, and public talks. Communication skills extend to the ability to craft grant proposals that persuade and to present findings in ways that resonate with stakeholders, funding bodies, and the general public.

Continuous Learning and Adaptation

The field of science is continually changing, and staying updated with the latest research methods, tools, and technologies is vital. Leek encourages a mindset of ongoing learning and adaptation. This could mean engaging with new statistical software, learning programming languages relevant to one’s field, or staying abreast of methodological advancements. The modern scientist must be a lifelong learner, always ready to incorporate new knowledge and techniques into their repertoire.

Conclusion

Jeff Leek's "How to Be a Modern Scientist" is more than a manual; it is a manifesto for rethinking the approach to scientific research in the 21st century. By fostering data literacy, embracing open science, adhering to ethical standards, honing communication skills, and committing to continuous learning, scientists can remain at the forefront of discovery and innovation. These practices not only enhance individual research but also propel the scientific community towards more collaborative, transparent, and impactful contributions to society