A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.
- notebooks
- python
- data-science
- machine-learning
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Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of intelligence based strictly on the neuroscience of the neocortex.
- neocortex
- artificial-intelligence
- machine-intelligence
- hierarchical-temporal-memory
Chronos: Pretrained Models for Time Series Forecasting
- forecasting
- large-language-models
- llm
- machine-learning
Probabilistic time series modeling in Python
- time-series
- deep-learning
- forecasting
- neural-networks
Time series forecasting with PyTorch
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
- machine-learning
- economics
- causal-inference
- causality
🕵 Artificial Intelligence for social control of public administration | **This repository does not receive frequent updates. Check out the README**
SQL Translator is a tool for converting natural language queries into SQL code using artificial intelligence. This project is 100% free and open source.
- data-analysis
- data-engineering
- dataquery
- datascience
NeuralProphet: A simple forecasting package
- forecasting
- time-series
- machine-learning
- fbprophet
TimeGPT-2.1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.
- time-series
- time-series-forecasting
- deep-learning
- forecasting
The Go kernel for Jupyter notebooks and nteract.
- go
- golang
- jupyter
- jupyter-notebook
🚀 Curated collection of Amazing Python scripts from Basics to Advance with automation task scripts.
- projects
- python-projects
- machine-learning
- artificial-intelligence
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
- python
- machine-learning
- explainability
- explainable-ml
Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) by way of Textual Inversion (https://arxiv.org/abs/2208.01618) for Stable Diffusion (https://arxiv.org/abs/2112.10752). Tweaks focused on training faces, objects, and styles.
Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data integrations. Use Python, R, and SQL locally in your favorite IDE, then scale to Deepnote cloud for real-time collaboration, Deepnote agent, and deployable data apps. https://deepnote.com/
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
- ai
- fairness-ai
- fairness
- fairness-testing
moDel Agnostic Language for Exploration and eXplanation
- machine-learning
- interpretability
- data-science
- xai