Practice and tutorial-style notebooks covering wide variety of machine learning techniques

Querybook is a Big Data Querying UI, combining collocated table metadata and a simple notebook interface.

Rendering IPython Notebooks using Flask

Python Machine Learning (ML) project that demonstrates the archetypal ML workflow within a Jupyter notebook, with automated model deployment as a RESTful service on Kubernetes.

This repository contains Jupyter Notebooks showcasing different techniques for price prediction using Artificial Neural Networks (ANNs). Topics covered include early stopping, batch normalization, dropout regularization, and deep neural networks. These notebooks offer practical implementations and insights for improving model training

Data Science AI Artificial Intelligence Deep Learning Python Keras TensorFlow TensorFlow2 Flask Flask3 Docker NGINX Gunicorn microservices REST API Jupyter Lab Notebook GitHub Actions Ruff

💰 Scraping, Visualizing, and Analyzing 1,700,000 Entries of Used Cars for Sale on Craigslist to Find The Best Car Deal 🚗

DiscreetAI’s service for generating and allocating customized Jupyter Notebooks for users.

A vue + flask based notebook and task manager

📓 Web app for storing Flash Cards related to Software Engineering. - Flask, SQLAlchemy

Notebook app made with Flask, a Python Web application framework for Back-end. And HTML/CSS, JavaScript for Front-end. Demo: https://a-notebook-app.herokuapp.com/

Racine - A collaborative lab book in your web browser

Fine-tune BERT for sentiment analysis. I have done text preprocessing (special tokens, padding, and attention masks) and build a Sentiment Classifier using the amazing Transformers library by Hugging Face! I have train my model on kaggle notebook on gpu. The model give the accuracy of 95.14% on validation dataset.

Collaborated to create a Machine Learning model trained and tested with a Random Forest model to predict primary emotion based on input audio file. Data cleaned and trained in a Jupyter Notebook using Pandas and Librosa. Results visualized using Pandas, Tableau, and JavaScript functions with bootstrap in a dynamic HTML website.

A calendar to mark something.

Unveil the magical formula behind wonderful quest generation of the overall storyline!

NR - Local Food Preferences with FLASK! (HTML, CSS, JS, SCSS, Python and Jupyter Notebook)

Web scraping using Jupyter Notebook, BeautifulSoup, Pandas, and Requests/Splinter. MongoDB with Flask templating to create a new HTML page

Yet another jupyter notebook server for custom REST endpoints.

In this project,we predict the car price using linear regression.