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Chris Kuo/Dr. Dataman
Chris Kuo/Dr. Dataman

5K Followers

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Dataman in AI

·Pinned

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

Anomaly detection is the detection of any rare events that deviate significantly from the majority of the data. Those rare events do not conform to a well-defined behavior. They are also called Outliers, noises, novelties, or exceptions. Rare events can detrimentally impact the business operation and result in a significant…

Data Science

16 min read

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

16 min read


Published in

Dataman in AI

·Pinned

Explain Your Model with the SHAP Values

Better Interpretability Leads to Better Adoption Is your highly-trained model easy to understand? A sophisticated machine learning algorithm usually can produce accurate predictions, but its notorious “black box” nature does not help adoption at all. Think about this: If you ask me to swallow a black pill without telling me…

Machine Learning

13 min read

Explain Your Model with the SHAP Values
Explain Your Model with the SHAP Values
Machine Learning

13 min read


Published in

Dataman in AI

·Pinned

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

Image classification is the task to recognize an image. It is also called image recognition. Computer scientists have been innovative in extracting meaning from images. Its history is fascinating, though most people don’t know much about it. For this reason, I am going to tell you the stories of innovation…

Data Science

13 min read

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

13 min read


Published in

Dataman in AI

·Pinned

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 accuracy. As humans, we must be able to fully understand how decisions are being made so that we can trust the decisions of AI systems. We need ML models to…

Data Science

9 min read

The SHAP Values with H2O Models
The SHAP Values with H2O Models
Data Science

9 min read


Published in

Dataman in AI

·Pinned

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 still feel uncertain. Since there are already many similar articles, why do I dare to add an article to this crowded topic? In this article, I re-write many ordinary answers…

Data Science

18 min read

Top Data Science Interview Questions and Answers
Top Data Science Interview Questions and Answers
Data Science

18 min read


Published in

Dataman in AI

·Oct 21

Search Like Light Speed — (2) LSH

In “Search like light speed — (1) HNSW,” we have learned Approximate Nearest Neighbors (ANN) and the graph-based Hierarchy Navigable Small World (HNSW) algorithm. In this post, we will learn the hashing-based Local-Sensitivity Hashing (LSH) algorithm. If you have not heard about hashing — do not worry. I will start…

Data Science

16 min read

Search Like Light Speed — (2) LSH
Search Like Light Speed — (2) LSH
Data Science

16 min read


Published in

Dataman in AI

·Oct 20

Search Like Light Speed — (1) HNSW

I love “Buzz Lightyear” the space ranger in Toy Story and I love his catchphrase “To infinity and beyond!” When I search for information, I also enjoy the speed of finding the right information. Is it all about high-speed internet and sufficient bandwidth? Not quite! In fact, the algorithms for…

Data Science

27 min read

Search Like Light Speed — (1) HNSW
Search Like Light Speed — (1) HNSW
Data Science

27 min read


Aug 21

Macroeconomics for investors — the 2008 recession

The 2008 recession, often referred to as the Global Financial Crisis, was a profound economic contraction that stemmed from a convergence of factors in the financial and housing sectors. It was characterized by the bursting of the U.S. housing bubble, triggered by excessive subprime mortgage lending and subsequent foreclosures. This…

Economy

17 min read

Macroeconomics for investors — the 2008 recession
Macroeconomics for investors — the 2008 recession
Economy

17 min read


Jul 22

Practical algorithmic trading — (1) Why algo trading and technical indicators?

Everyday there are millions of data analysts, data scientists, data engineers, or quants who analyze various financial factors for their investment decisions. Algorithmic trading, the use of computer algorithms to automate the process of buying and selling financial securities in the markets, is the major channel of investment in today’s…

Algorithmic Trading

13 min read

Practical algorithmic trading — (1) Why algo trading and technical indicators?
Practical algorithmic trading — (1) Why algo trading and technical indicators?
Algorithmic Trading

13 min read


Jul 22

Practical Algorithmic Trading — (2) Backtesting

We may have a brilliant trading strategy, but without testing the strategy we are still not sure if it will work. Backtesting is the best sandbox for us to conduct testing, called paper trading. It applies a trading strategy to historical market data to determine how it would have performed…

Algorithmic Trading

15 min read

Practical Algorithmic Trading — (2)  Backtesting
Practical Algorithmic Trading — (2)  Backtesting
Algorithmic Trading

15 min read

Chris Kuo/Dr. Dataman

Chris Kuo/Dr. Dataman

5K Followers

The Dataman articles are my reflections on data science and teaching notes at Columbia University https://sps.columbia.edu/faculty/chris-kuo

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