Breast Cancer Diagnosis using machine learning algorithms | Deep Learning | Logistic Regression | API | Frontend | Backend |
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Updated
Jul 11, 2019 - CSS
Breast Cancer Diagnosis using machine learning algorithms | Deep Learning | Logistic Regression | API | Frontend | Backend |
Breast Cancer Classifier using Logistic Regression
This is an Web Application to predict the IPL Match winner.
In statistics, the logistic model (or logit model) is used to model the probability of a certain class or event existing such as pass/fail, win/lose, alive/dead or healthy/sick. This can be extended to model several classes of events such as determining whether an image contains a cat, dog, lion, etc. Each object being detected in the image woul…
Logistic Regression model trained to determine if someone will survive the Titanic disaster, dressed in a Flask API and deployed on Heroku.
Sentiment Analysis of Tweets During Covid Period https://infysoars-project-covid.infysoars.repl.co/dashboard
Twitter Sentiment Analysis is a mini project that utilizes Logistic Regression to classify tweets as either positive or negative. The project includes an API endpoint built with FastAPI, allowing users to submit a tweet's URL and receive a sentiment analysis response.
This project aims to predict the type 2 diabetes, based on the dataset. It uses machine learning model,which is trained to predict the diabetes mellitus before it hits.
This Project will help us to make better choices the appropriate crop for the soil based on several factors.
An educational sandbox to help understand Logistic Regression from a more intuitive perspective.
This project is a development of Flask Application called 'Know It' which consists of three different prediction codes which are Pizza Liking Prediction, Fuel Price Prediction and Diabetes Prediction.
Interactive Visual Machine Learning Demos.
This project objective is to predict the type 2 diabetes, based on the dataset.
Project FITA: Fires in the Amazon. WebApp para análise e classificação de imagens de satélite da Amazônia.
This is a Django application for predicting whether the sentiment of a financial news headline is positive, negative or neutral (from an investor point of view)
Portfolio projects
Attended the LanHack conducted by Lancaster University - Lancaster, UK and developed a ML-based model to classify Malicious and Non-Malicious URLs.
Login-registration form, design
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