Dan Romuald Mbanga's starred repositories
Awesome-LLM-Robotics
A comprehensive list of papers using large language/multi-modal models for Robotics/RL, including papers, codes, and related websites
vertex-ai-alphafold-inference-pipeline
This repository compiles prescriptive guidance and code samples demonstrating how to operationalize AlphaFold batch inference using Vertex AI Pipelines.
generative-ai
Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI
Awesome-Diffusion-Models
A collection of resources and papers on Diffusion Models
vegawallet
Command-line tool to manage your Vega Protocol wallet, a protocol for creating and trading derivatives on a fully decentralised network.
Cryptofolio
Track your cryptocurrency holdings/portfolio with an open-source web, mobile, and desktop application, along with a self-hosted RESTful API.
qlib
Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.
savetheworldwithgo
Build systems with Go examples
Hands-On-Software-Engineering-with-Golang
Hands-On Software Engineering with Golang, published by Packt
schuller-geometric
Source code for lecture notes
Practical_RL
A course in reinforcement learning in the wild
Twitter_Analytics
Source code for blog post: An Introduction to Text Mining using Twitter Streaming API and Python
ai-workshop
Artificial Intelligence Workshop
sagemaker-tensorflow-training-toolkit
Toolkit for running TensorFlow training scripts on SageMaker. Dockerfiles used for building SageMaker TensorFlow Containers are at https://github.com/aws/deep-learning-containers.
deepmersion
own your surroundings
a-trip-down-lstm-lane
Textual generation using character LSTMs
sagemaker-spark
A Spark library for Amazon SageMaker.
mxnet-ccn-samples
Mxnet-cnn-samples
lambda-refarch-imagerecognition
The Image Recognition and Processing Backend reference architecture demonstrates how to use AWS Step Functions to orchestrate a serverless processing workflow using AWS Lambda, Amazon S3, Amazon DynamoDB and Amazon Rekognition.