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Missing data visualization module for Python.
The Virtual Feature Store. Turn your existing data infrastructure into a feature store.
Awesome curated RSS feed links related to Machine Learning, Artificial Intelligence, Reinforcement Learning
Time series easier, faster, more fun. Pytimetk.
Friendly Adblock for YouTube: A fast, lightweight, and undetectable YouTube Ads Blocker for Chrome, Opera and Firefox.
A Library for Advanced Deep Time Series Models.
About Code release for "Flowformer: Linearizing Transformers with Conservation Flows" (ICML 2022), https://arxiv.org/pdf/2202.06258.pdf
About Code release for "TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis" (ICLR 2023), https://openreview.net/pdf?id=ju_Uqw384Oq
Source code of paper: GBT: Two-stage Transformer Framework for Non-stationary Time Series Forecasting.
The Dom amongst the Flipper Zero Firmware. Give your Flipper the power and freedom it is really craving. Let it show you its true form. Dont delay, switch to the one and only true Master today!
Playground (and dump) of stuff I make or modify for the Flipper Zero
Flipper Zero Unleashed Firmware
Python Data Science Handbook: full text in Jupyter Notebooks
A library for efficient similarity search and clustering of dense vectors.
Time series forecasting with machine learning models
Calculates various features from time series data. Python implementation of the R package tsfeatures.
The aim was to create and implement a predictive model that can forecast the number of items sold for a period of 8 weeks ahead.
mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.
Code for the paper "Language Models are Unsupervised Multitask Learners"
A playbook for systematically maximizing the performance of deep learning models.
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
Original Apollo 11 Guidance Computer (AGC) source code for the command and lunar modules.
High-level information such as: number of panelists each day, can be used in order to identify outlier periods by using simple transformations and indexes. The project is a practical example of ide…