Feature Engineering and Predictive Modeling for Financial Time Series Data

This repository shows an example of the usability of SKORCH to train a PyTorch model making use of different capabilities of the scikit-learn framework.

Deep Learning (PyTorch) Models Deployment using SQL databases

Your digital assistant for meeting new people 👬🏼

Utilities for scikit-learn. Append prediction to x, append prediction to x single, append x prediction to x, compose var estimator, data frame wrapper, drop by noise prediction, drop missing rows y, dummy regressor var, estimator wrapper base, excluded column transformer pandas, feature union pandas, id transformer, included column transformer pand

Train a simple CNN for handwritten digit classification.

PyTorch application for regression task

Notebook to show the usage of skorch to wrap PyTorch models for making them sklearn compatible.

A neural network-based crop recommendation system leveraging soil and environmental data. Achieved 98% accuracy through hyperparameter tuning and evaluation of two architectures with 2 and 5 hidden layers.

Jacobian regularisation for neural networks (PyTorch) and hyperparameter tuning with Skorch

A microservices-based architecture bank application that includes back-end and front-end applications, as well as a binary classification model, smart contracts to store data on-chain and TheGraph subgraphs.

Build machine learning model to predict the character of each image.