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…

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…

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…

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…

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…

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…

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…

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…

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…