ggsdc
Project manager, product development and data scientist at baobab soluciones. MSc in Artificial Intelligence.
baobab solucionesMadrid, Spain
ggsdc's Stars
berthubert/bnt162b2
Markdown version of Reverse Engineering the source code of the BioNTech/Pfizer SARS-CoV-2 Vaccine
matrix-profile-foundation/matrixprofile
A Python 3 library making time series data mining tasks, utilizing matrix profile algorithms, accessible to everyone.
StepNeverStop/RLs
Reinforcement Learning Algorithms Based on PyTorch
marshmallow-code/marshmallow-oneofschema
Marshmallow library extension that allows schema (de)multiplexing
aimacode/aima-python
Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
kailashahirwar/cheatsheets-ai
Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5
codecrafters-io/build-your-own-x
Master programming by recreating your favorite technologies from scratch.
AIStream-Peelout/flow-forecast
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
oliverguhr/transformer-time-series-prediction
proof of concept for a transformer-based time series prediction model
rasbt/python-machine-learning-book-3rd-edition
The "Python Machine Learning (3rd edition)" book code repository
rasbt/deeplearning-models
A collection of various deep learning architectures, models, and tips
tensorflow/decision-forests
A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.
DrKenReid/FactorioBeltProblemGECCO
A Factorio interface for optimizing belt layouts, offering installation instructions for Docker and Factorio, along with guidance on running optimizations using custom scripts.
tedivm/tedivms-flask
Flask starter app with celery, bootstrap, and docker environment
frictionlessdata/frictionless-py
Data management framework for Python that provides functionality to describe, extract, validate, and transform tabular data
OpenRailAssociation/osrd
An open source web application for railway infrastructure design, capacity analysis, timetabling and simulation
facebookresearch/CPA
The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell level. CPA performs OOD predictions of unseen combinations of drugs, learns interpretable embeddings, estimates dose-response curves, and provides uncertainty estimates.
lcswillems/rl-starter-files
RL starter files in order to immediately train, visualize and evaluate an agent without writing any line of code
graphql-python/graphene-django
Build powerful, efficient, and flexible GraphQL APIs with seamless Django integration.
larq/larq
An Open-Source Library for Training Binarized Neural Networks
ts2/ts2
TS2 - Train Signalling Simulator
yugedata/Options_Data_Science
Collecting, analyzing, visualizing & paper trading options market data
plasma-umass/scalene
Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals
ml-tooling/best-of-ml-python
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
apache/superset
Apache Superset is a Data Visualization and Data Exploration Platform
firmai/industry-machine-learning
A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)
onelivesleft/PrettyErrors
Prettify Python exception output to make it legible.
ruiqimao/keyboard-pcb-guide
Guide on how to design keyboard PCBs with KiCad
GiulioRossetti/ndlib
Network Diffusion Library - (for NetworkX and iGraph)
dcmocanu/sparse-evolutionary-artificial-neural-networks
Always sparse. Never dense. But never say never. A Sparse Training repository for the Adaptive Sparse Connectivity concept and its algorithmic instantiation, i.e. Sparse Evolutionary Training, to boost Deep Learning scalability on various aspects (e.g. memory and computational time efficiency, representation and generalization power).