[Not Actively Maintained] Whitebox is an open source E2E ML monitoring platform with edge capabilities that plays nicely with kubernetes

Experience predictive healthcare with our Streamlit app. Utilizing Random Forest, our tool analyzes medical data to assess diabetes risk swiftly. Ideal for healthcare professionals and researchers, this user-friendly app simplifies risk evaluation. Join us in the fight against diabetes.

Stock Price Prediction of APPLE Using Python

In this project, we aim to identify different fruits: apples, bananas, oranges, and tomatoes; through different Machine Learning algorithms: CNN, XGBoost, InceptionV3 transfer learning, and VGG16 transfer learning

This performs of evaluation of machine learning models with ease and provides the visualization

In this project we have created a spam classifier model on UCI dataset. We performed data cleaning and preprocessing, followed by Stemming and Bag of Words technique and finally developed a Naive Bayes Multinomial model.

Machine Learning course of Piero Savastano 4: CountVectorizer, BernoulliNB, accuracy_score, pandas

Machine Learning course of Piero Savastano 2: DecisionTreeClassifier, accuracy_score

The motive of this project is to find out the customer satisfaction of some residential hotels of Dhaka.

Performance calculation tool for Hateful Memes Challenge

company_data_prj9

Learning python day 4

Implementing Neural Network on Irish data - evaluating accuracy, Mean Squared Error (MSE), Crossentropy and log-likelihood

TakenMind Global Internship Program is recognized under United Nations Sustainable Development and Growth (SDG) and is a highly recognized International Certification Program. - Reference Link to the United Nations SDG #26437 TakenMind Program. TakenMind (powered by United Nations SDG Program) is offering a Global Internship in Data Analytics an…

Machine Learning course of Piero Savastano 6: scaling, MinMaxScaler, KNeighborsClassifier, accuracy_score

🗣️ Speech Type Detection is a Flask app to classifies text into categories like "Hate Speech," "Offensive Language," or "No Hate or Offensive Language" with 87.3% accuracy. It offers a user-friendly interface for text input and prediction, using machine learning algorithms. Idea for managing online inappropriate language. 🌐🔍.