Chris Kuo/Dr. Dataman

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Dataman in AI

Handbook of Anomaly Detection: With Python Outlier Detection — (1) Introduction

Anomaly detection is the detection for any rare events that deviate significantly from the majority of the data. Those rare events, called…

16 min readOct 9, 2022

Handbook of Anomaly Detection: With Python Outlier Detection — (1) Introduction

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Dataman in AI

Explain Your Model with the SHAP Values

Use the SHAP Values to Explain Any Complex ML Model

13 min readSep 14, 2019

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Transfer Learning for Image Classification — (2) Pre-trained Image Models

Hands on with Pre-trained models

13 min readJan 30, 2023

Transfer Learning for Image Classification — (2) Pre-trained Image Models

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The SHAP Values with H2O Models

Many machine learning algorithms are complicated and not easy to understand, even though they have rendered an impressive level of…

9 min readNov 24, 2021

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Prophet for Business Forecasting

Sample eBook chapters (free): https://github.com/dataman-git/modern-time-series/blob/main/20240522beauty_TOC.pdf

17 min readMay 10, 2024

Chris Kuo/Dr. Dataman

Learn NLP the Easy Way — Text Representation

Gensim, NLTK, Scikitlearn

21 min readMay 9, 2024

Learn NLP the Easy Way — Text Representation

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Dataman in AI

Change Point Detection in Time Series

Sample eBook chapters (free): https://github.com/dataman-git/modern-time-series/blob/main/20240522beauty_TOC.pdf

12 min readMay 6, 2024

Chris Kuo/Dr. Dataman

Deep Learning-based DeepAR for Time Series Probabilistic Forecasting

Real-world applications bring forth innovations for time series forecasting. Here let’s consider two use cases. An electricity company…

14 min readMay 4, 2024

Deep Learning-based DeepAR for Time Series Probabilistic Forecasting

Chris Kuo/Dr. Dataman

Two Primary Strategies for Multi-period Time Series Forecasting

Sample eBook chapters (free): https://github.com/dataman-git/modern-time-series/blob/main/20240522beauty_TOC.pdf

11 min readMay 1, 2024

Two Primary Strategies for Multi-period Time Series Forecasting

Handbook of Anomaly Detection: With Python Outlier Detection — (1) Introduction

Anomaly detection is the detection for any rare events that deviate significantly from the majority of the data. Those rare events, called…

Explain Your Model with the SHAP Values

Use the SHAP Values to Explain Any Complex ML Model

Transfer Learning for Image Classification — (2) Pre-trained Image Models

Hands on with Pre-trained models

The SHAP Values with H2O Models

Many machine learning algorithms are complicated and not easy to understand, even though they have rendered an impressive level of…

Top Data Science Interview Questions and Answers

You receive a data science interview opportunity from your dream company. You have surveyed many the-top-50-question types of articles but…

Prophet for Business Forecasting

Sample eBook chapters (free): https://github.com/dataman-git/modern-time-series/blob/main/20240522beauty_TOC.pdf

Learn NLP the Easy Way — Text Representation

Gensim, NLTK, Scikitlearn

Change Point Detection in Time Series

Sample eBook chapters (free): https://github.com/dataman-git/modern-time-series/blob/main/20240522beauty_TOC.pdf

Deep Learning-based DeepAR for Time Series Probabilistic Forecasting

Real-world applications bring forth innovations for time series forecasting. Here let’s consider two use cases. An electricity company…

Two Primary Strategies for Multi-period Time Series Forecasting

Sample eBook chapters (free): https://github.com/dataman-git/modern-time-series/blob/main/20240522beauty_TOC.pdf

Chris Kuo/Dr. Dataman