Emmanuel Bonnet's Projects
Repository for hyperparameter tuning
Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.
A Python framework for creating reproducible, maintainable and modular data science code.
Deep Learning for humans
Kestra is an infinitely scalable orchestration and scheduling platform, creating, running, scheduling, and monitoring millions of complex pipelines.
The package inherits from sklearn.cluster.KMeans and can be used in the same way with the addition of feature_importances_ property
Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data
[EOL] A command-line tool to declaratively manage Kubernetes clusters on AWS
Issue tracker and mirror of kubectl code
Kubernetes Cluster Federation
Machine Learning Toolkit for Kubernetes
šļø LabelImg is a graphical image annotation tool and label object bounding boxes in images
Git-like capabilities for your object storage
140523
Port of Google's language-detection library to Python.
Using advanced MIP decomposition techniques like Column Generation, Benders' Decomposition, Lagrangian Relaxation to solve CVRP and UFL with Gurobi (Python API) and CPLEX (C++ Concert Technology)
LAVIS - A One-stop Library for Language-Vision Intelligence
Implementation of Layerwise Relevance Propagation for heatmapping "deep" layers
A Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment
Learn Apache Airflow in easy way
š Playground and cheatsheet for learning Python. Collection of Python scripts that are split by topics and contain code examples with explanations.
Jupyter notebooks for teaching/learning Python 3
For learning stuff & for experimentation
Code repository associated with Learning Algorithms: A Programmer's Guide to Writing Better Code. https://oreil.ly/learn-algorithms
Learn Python with LetUsDevOps
This Project Describes the LC Solutions for all the SQL Problems solved by me šāØ
Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems).
LightweightMMM š¦ is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information. The library also includes capabilities for optimizing media allocation as well as plotting common graphs in the field.
The Language Interpretability Tool: Interactively analyze NLP models for model understanding in an extensible and framework agnostic interface.
Inference code for genesis models