Best for beginners | Well explained ML algorithms | organized Notebooks | Case Studies
-
Updated
May 28, 2024 - Jupyter Notebook
Best for beginners | Well explained ML algorithms | organized Notebooks | Case Studies
This notebook describes how to compute and derive insights from various classification evaluation metrics.
Jupyter notebook showing how to build an image classifier with Python and Tensorflow
This repository contains my collections of labs' notebooks from Udacity's Intro to ML with TensorFlow.
Code for classifying breast cancer tumors using machine learning. Includes preprocessing, visualizations, and models like Logistic Regression, Decision Tree, and Random Forest. Evaluated with accuracy, precision, recall, and F1-score. Clone, install dependencies, and run the Jupyter notebook for full analysis.
This repo contains notebooks for building a dataset with Spotify personal listening data, EDA and creating a model which classifies songs from personal listening history vs a random sample
This repository is a series of notebooks that show analysis and modeling of the Breast Cancer data from Kaggle.
Evaluates a binary text classification notebook where GenAI misclassified labels. Demonstrating understanding of precision and recall allows for effective problem-solving and proposes threshold adjustments to improve model performance.
Add a description, image, and links to the recall topic page so that developers can more easily learn about it.
To associate your repository with the recall topic, visit your repo's landing page and select "manage topics."