Scott Schmidt's repositories
amazon-rekognition-custom-labels-batch-processing
This project contains source code and supporting files for a serverless application which can be used for Computer Vision inferencing using Amazon Rekognition.
Amazon-SageMaker-Best-Practices
Amazon SageMaker Best Practices, published by Packt
amazon-sagemaker-examples
Example notebooks that show how to apply machine learning and deep learning in Amazon SageMaker
aws-data-wrangler
Pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
aws-lambda-developer-guide
The AWS Lambda Developer Guide
aws-tkcimages-pipeline
Process images and videos at scale using Amazon Rekognition
documentdb-sagemaker-example
We use Amazon SageMaker to analyze data stored in Amazon DocumentDB. After showing how to write queries to conduct a descriptive analysis, we build a simple machine learning model to make predictions, then we write the prediction results back into the database.
gpt4all
gpt4all: a chatbot trained on a massive collection of clean assistant data including code, stories and dialogue
HuggingFacenotebooks
Notebooks using the Hugging Face libraries 🤗
isowords
A word search game on a vanishing cube, built in SwiftUI and the Composable Architecture.
Learn-Amazon-SageMaker-second-edition
Learn Amazon SageMaker - Second Edition, published by Packt
makemore
An autoregressive character-level language model for making more things
nanoGPT
The simplest, fastest repository for training/finetuning medium-sized GPTs.
NLPwTransformer-notebooks
Jupyter notebooks for the Natural Language Processing with Transformers book
nn-zero-to-hero
Neural Networks: Zero to Hero
openai-quickstart-node
Node.js example app from the OpenAI API quickstart tutorial
OpenBBTerminal
Investment Research for Everyone, Anywhere.
practical-haskell
Source Code for 'Practical Haskell' by Alejandro Serrano Mena
scala3-example-project
An example sbt project that compiles using Dotty
ServerlessDemo
Developing Serverless APIs using AWS Toolkit
transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Transformers-for-NLP-2nd-Edition
Under the hood working of transformers, fine-tuning GPT-3 models, DeBERTa, vision models, and the start of Metaverse, using a variety of NLP platforms: Hugging Face, OpenAI API, Trax, and AllenNLP
vim_reference
:q Vim reference guide for beginner to intermediate users
vis-network
:dizzy: Display dynamic, automatically organised, customizable network views.