Photo by Eugene Machiavelli for Shakuro on Dribbble You’ll want to evaluate almost every model you ever build. In most (though not all) applications, the relevant measure of model quality is predictive accuracy. In other words, will the model’s predictions be close to what actually happens. Many people make a huge mistake when measuring predictive accuracy. …
Photo by MUTI on Dribbble Context Access to safe drinking-water is essential to health, a basic human right and a component of effective policy for health protection. This is important as a health and development issue at a national, regional and local level. In some regions, it has been shown that investments in water supply and …
Water Potability Test using Deep Neural Networks Read More »
Photo by LISTENXU on Dribbble TABLE OF CONTENTS 1. IMPORTING DATA 2. LOADING DATA 3. DATA VISUALIZATION AND TECHNIQUES 4. DATA PREPROCESSING 5. MODEL BUILDING 6. CONCLUSION 7. End IMPORTING LIBRARIES LOADING DATA ABOUT THE DATA Context Predict next-day rain by training classification models on the target variable Rain Tomorrow. Content This dataset contains about 10 years …
Photo by Manu Designer on Dribbble Fingerprint, as a unique feature of each person, can be divided into different types. In this project, we identify real fingerprints pattern and classify them with convolutional neural networks(CNN). Dataset The dataset is the original NIST 8-Bit Gray Scale Images of Fingerprint Image Groups(FIGS). It comprises 4000 images that are …
Fingerprint pattern classification using Deep Learning Read More »
Photo by Ahmed Maghrabi on Dribbble Classification is the categorization of the object based on defined classes.. Introduction Object Detection is one of the most famous and extensively researched topics in the field of Machine Vision. To understand Object Detection in simplistic terms, it deals with identifying and localizing some of the classes such as person, …
Object Classification(Electric Car and Electric Bus Classification) Read More »
Photo by Margarita Ivanchikova on Dribbble 100 triangles, 100 squares, and 100 circles in processing. each png image is 28×28 px, the images are in 3 folders labeled squares, circles, and triangles pretty straightforward We have to find the shape that falls in its category by training the model using Neural Networks. Importing Libraries Unzipping the data …
Photo by Jonas Mosesson on Dribbble Introduction Tomato Disease Detection with CNN Architecture – The aim of this project is to identify various diseases on tomatoes based on their leaves. It is very important in agriculture to identify diseases immediately. To detect the problem in real time, we develop Deep Learning model that can be installed …
Photo by Mat Voyce on Dribbble Are the most common cause of deaths globally, taking an estimated 17.9 million lives each year, which accounts for 31% of all deaths worldwide. Heart failure is a common event caused by Cardiovascular diseases. It is characterized by the heart’s inability to pump an adequate supply of blood to the …