Repository to try to learn how to do anomaly detection with Python. Included here are Jupyter notebook as well.
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Updated
Apr 29, 2015 - Python
Repository to try to learn how to do anomaly detection with Python. Included here are Jupyter notebook as well.
Bootlier implementation for anomaly detection
Machine Learning exercises in Python (Jupyter notebooks)
ISOLATION FOREST ALGORITHM FOR PIEZO DATA
This notebook demonstrates how to use the Microsoft Azure Anomaly Finder Service.
iPython notebook and pre-trained model that shows how to build deep Autoencoder in Keras for Anomaly Detection in credit card transactions data
Detection of Accounting Anomalies using Deep Autoencoder Neural Networks - A lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.
Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks - A lab we prepared for the KDD'19 Workshop on Anomaly Detection in Finance that will walk you through the detection of interpretable accounting anomalies using adversarial autoencoder neural networks. The majority of the lab content is based on J…
Anomaly Detection in the Wild -- presentation and notebook for PyCon Canada 2019
Anomaly detection notebook
Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)
Repository contains notebooks with some AI related problems and sometimes not
Machine learning Python notebooks based on the ML Course assignments
Simulated bad pixels from the NIR HxRG detector suite on the HST, JWST, and Roman Space Telescope. Using these simulations, notebooks here provide tools to train LSTM and Conv1D deep learning models to build Anomaly Detectors for HxRG bad pixels
A notebook about credit card fraud detection treated as anomaly detection via multivariative normal distribution. The dataset is highly imbalanced (0.17 % of positive class labels). Dataset source: https://www.kaggle.com/mlg-ulb/creditcardfraud
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BER
Jupyter notebooks implementing Machine Learning algorithms in Scikit-learn and Python
In this repo, I have uploaded all the projects that I made while learning ml techniques and are a good start for beginners. You can use them as well to learn.
A notebook using many unsupervised learning techniques. PCA, K-means, Gaussian Mixtures. Clustering, dimensionality reduction, anomaly detection
Data Science notebooks
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