Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Jupyter notebooks demonstrating setup and use of the R-ArcGIS bridge. The repo includes datasets required to run the Jupyter notebooks.
Example notebooks for working with SageMaker Studio Lab. Sign up for an account at the link below!
The notebook explains the various steps to obtain the results of publication: "Is Space-Time Attention All You Need for Video Understanding?"
A trio of Google-Colab notebooks (ipynb) for training a GPT-2 (127M) model from scratch (useful for other / non-English languages) using gpt-2-simple
pytorch notebook for implemention for cut-cross-entropy LLM training.
A basic machine learning model built in python jupyter notebook to classify whether a set of tweets into two categories: racist/sexist non-racist/sexist.
Paparspace notebook for kohya gui lora training
This repository contains mini project in machine learning with notebook files
@yamilesquivel , drawings and efect over images
Jupyter notebook for creating Research Object in ROHub for defining a checklist for master students.
I gave training on ML and DL. This repository contains notes from that training as jupyter notebooks.
Can be used as-is for better slashed zeros recognition (especially with the Consolas font). This Repository includes a Jupyter notebook with instructions to train/finetune a Tesseract OCR model.
This notebook is designed to train a deep learning model for face emotion recognition. It uses TensorFlow and is run in a Google Colab environment.
This notebook sets up MLFlow for experiment tracking, including data preprocessing, training a random forest regressor, logging metrics and parameters, hyperparameter optimization with hyperopt, and model registration. It provides steps for environment setup and installation.
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