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airflow-tutorial

Apache Airflow tutorial

al-folio

A beautiful, simple, clean, and responsive Jekyll theme for academics

applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

aps2020tutorial

Tutorial on image analysis with deep / machine learning for APS-2020 meeting in Denver

attention_keras

Keras Layer implementation of Attention

color-compression-unsupervised-ml

Color image compression using unsupervised Machine Learning algorithms. In this project, functions are defined to compress the images using k-means, winner takes all and Kohonen maps.

customer-churn-analysis

In this project, the growth team at Y aimed to understand why users withdraw money from their Y accounts and identify which users are likely to churn. By analyzing the provided datasets, we built and evaluated a classifier to predict user churn, ultimately classifying each user in the dataset based on their likelihood to leave.

diabetes-prediction

Developed a ML algorithm to predict/classify an unknown dataset containing the collected details of women under 21 of Pima Indian heritage, living near Phoenix, Arizona. The training data is collected from Ripley's Pattern Recognition and Neural Networks website.

fellow-placement

first-contributions

🚀✨ Help beginners to contribute to open source projects

fraud-detection

graph-enumeration

This is a code to enumerate the number of graphs from a liquid system model.

hello-world

This is my first code in GitHub.

kaggle-comps

llms-from-scratch

Implementing a ChatGPT-like LLM from scratch, step by step

loan-application-prediction

The dataset includes application data for every customer that has been given a loan in a 6 month period. The other contains every loan that has been given in this time and whether it has been a good loan or a bad loan. Use the data to identify which new applicants should be given a loan in the future.

ludwig

Ludwig is a toolbox that allows to train and evaluate deep learning models without the need to write code.

machine-learning-engineering-for-production-public

Public repo for DeepLearning.AI MLEP Specialization

ml_models

mlframework

mobilephone-price-prediction

Supervised and unsupervised ML algorithms for classifying mobile phones based their features to 4 different categories based their market prices.

molecular-dynamics-postprocessing

Scripts for post-processing the output files from Molecular Dynamics simulations (Classical & Ab-initio MD)

montecarlomarkovchain

This Toy project aims to use MCMC methods to estimate the parameters of a Bayesian model and make inferences about the relationships between variables.

perceptron

Perceptron is a supervised machine learning approach using binary classifiers. Here, we try to create an algorithm to create a Perceptron using Gradient Descent approach. Simple logic gate data will be used to test the accuracy of the perceptron.

ragfeynman

RAGFeynman is a question-answering assistant that leverages Retrieval-Augmented Generation (RAG) with large language models (LLMs) like Gemma or TinyLlama. This application uses a variety of tools and libraries to provide accurate and efficient answers to user queries.

recommender-systems

sports-segementation

computer vision and sports

stock-trading-ml

A stock trading bot that uses machine learning to make price predictions.

streamlit

This is a Streamlit-based web application that allows users to predict the species of an Iris flower based on its sepal length, sepal width, petal length, and petal width. The app uses a pre-trained machine learning model to make the predictions.

supervised-machine-learning-on-normalized-data

Some supervised machine learning algorithms are created from basic principles to study and classify a normalized synthetic data from Pattern Recognition and Neural Networks by b. D. Ripley (https://www.stats.ox.ac.uk/pub/PRNN/)