Quantitative analysis of fundamentals in quarterly reports by Machine Learning
A project showcasing the various steps involved in carrying out a basic linear regression task for prediction of a target variable.
This project uses deep learning models to recognize landmarks and monuments, leveraging MobileNetV2 for landmark predictions and a custom CNN for monument classification. It provides functionalities for data visualization, training, and prediction, making it a comprehensive solution for image-based recognition tasks.
Statistical Analysis, Discriminatory power using t-test, Train/Test set, Prediction by Voting mechanism for global accuracies.
Auto Github ECR push, CML to trigger EC2 spot, DVC Repro S3 storage using github actions, Deploy using Gradio to hugging face spaces - The School of AI EMLO-V4 course assignment https://theschoolof.ai/#programs
In this project i will show you how you can find circles in a image plus recognize digits using knn and finally arrange the recognized digits in ascending order and click on those circles in sequencially
Add a description, image, and links to the train-test topic page so that developers can more easily learn about it.
To associate your repository with the train-test topic, visit your repo's landing page and select "manage topics."