Alternatives and similar repositories for Handbook-of-anomaly-detection

Users that are interested in Handbook-of-anomaly-detection are comparing it to the libraries listed below

• marcopeix / TimeSeriesForecastingUsingFoundationModels
  Official repository for the book Time Series Forecasting with Foundation Models
  ☆23Updated last week
• KishManani / m5-forecasting-tutorial
  An end-to-end tutorial to forecast the M5 dataset using feature engineering pipelines and gradient boosting.
  ☆19Updated 2 years ago
• PacktPublishing / Accelerate-Deep-Learning-Workloads-with-Amazon-SageMaker
  Accelerate Deep Learning Workloads with Amazon SageMaker, published by Packt
  ☆17Updated last year
• marcopeix / intermittent_time_series
  ☆13Updated last year
• grahamharrison68 / Public-Github
  Repository for GH public projects
  ☆18Updated last year
• PacktPublishing / Python-Feature-Engineering-Cookbook-Third-Edition
  Python Feature Engineering Cookbook, Third Edition, published by Packt
  ☆55Updated last month
• tblume1992 / TSUtilities
  Various utilities for time series forecasting
  ☆10Updated 2 years ago
• PacktPublishing / XGBoost-for-Regression-Predictive-Modeling-and-Time-Series-Analysis
  XGBoost for Regression Predictive Modeling and Time Series Analysis, published by Packt
  ☆33Updated last month
• marcopeix / AppliedTimeSeriesForecastingInPython
  Repository with data, starter notebooks, and solution notebooks for my course Applied Time Series Forecasting in Python
  ☆51Updated 5 months ago
• massi82 / multi-armed-bandit
  ☆13Updated last year
• TsLu1s / tsforecasting
  TSForecasting: Automated Time Series Forecasting Framework
  ☆28Updated 7 months ago
• saritmaitra / Segmentation-Clustering
  Recency, Frequency, and Monetary are three behavioral attributes and are quite simple, in that they can be easily computed for any databa…
  ☆15Updated last year
• vaexio / dash-predictive-maintenance-app
  Dash web app showing when an engine is expected to fail powered by vaex and tf/keras.
  ☆18Updated 3 years ago
• smasis001 / odsc-west-2022
  Workshop for Open Data Science Conference East 2022
  ☆10Updated 2 years ago
• smazzanti / valicast
  Validation for forecasts
  ☆18Updated 2 years ago
• ElizaLo / Time-Series
  Awesome list and projects of Time Series
  ☆29Updated last year
• khuyentran1401 / prefect-docker
  Demo on how to use Prefect with Docker
  ☆25Updated 2 years ago
• h3ik0th / ES_energy_Transformer
  Python Darts deep forecasting models
  ☆33Updated 3 years ago
• BartoszSzablowski / Sell_Out_Sell_In_Forecasting
  Sell Out Sell In Forecasting project implemented at Nestlé
  ☆23Updated 3 years ago
• PacktPublishing / Machine-Learning-for-Streaming-Data-with-Python
  Machine Learning for Streaming Data with Python, published by Packt
  ☆71Updated last year
• se-jaeger / conformal-data-cleaning
  Code for the AISTATS 2024 Paper "From Data Imputation to Data Cleaning - Automated Cleaning of Tabular Data Improves Downstream Predictiv…
  ☆22Updated last year
• KishManani / PyDataLondon2022
  Slides for "Feature engineering for time series forecasting" talk
  ☆60Updated 2 years ago
• Brett-Kennedy / CountsOutlierDetector
  Interpretable, intuitive outlier detector intended for categorical and numeric data.
  ☆10Updated last year
• solegalli / Python-Feature-Engineering-Cookbook-Second-Edition
  ☆12Updated last year
• Valdecy / pyInterDemand
  A python Library for Intermittent Demand Methods: Croston, SBA, SBJ, TSB, HES, LES and SES
  ☆36Updated last year
• sujikathir / Intermittent-demand-forecasting
  Predicting the Sales using Time-series forecasting for month-wise data.
  ☆20Updated 4 years ago
• bits-bytes-nn / mofc-demand-forecast
  Time Series Forecasting for the M5 Competition
  ☆40Updated 3 years ago
• raz1470 / causal_ai
  This project introduces Causal AI and how it can drive business value.
  ☆47Updated 9 months ago
• solegalli / feature-selection-with-feature-engine-book
  Code repository for the book Feature engineering with Feature-engine
  ☆14Updated last year
• donlapark / coverforest
  A simple and fast sklearn-compatible conformal predictions with random forests for both classification and regression tasks.
  ☆44Updated 2 months ago