Visualization

摘要： The psychological habit most people lack and why you can’t hope to use data to guide your actions effectively without it

摘要： In this blog, we will unfold the key problems associated with classification accuracies, such as imbalanced classes, overfitting, and data bias, and proven ways to address those issues successfully.

摘要： The fastest way to diagnose your statistical alignment

摘要： The bias-variance tradeoff, part 2 of 3

In Part 1, we covered much of the basic terminology as well as a few key insights about the bias-variance formula (MSE = Bias² + Variance), including this paraphrase from Anna Karenina:

All perfect models are alike, but each unhappy model can be unhappy in its own way.

To make the most of this article, I suggest taking a look at Part 1 to make sure you’re well-situated to absorb this one.

摘要： The AI bias trouble starts — but doesn’t end — with definition. “Bias” is an overloaded term which means remarkably different things in different contexts.

摘要： 美國開國先賢富蘭克林曾經說過，「最重要的是要懂得如何使用新的技術與工具，而不一定要懂得其原理。」現在科學領域中最為迷人的「量子科技」或許就是最好的例子之一。

摘要： Even though one of the largest crypto exchanges, FTX, collapsed and filed for bankruptcy, some market participants aren’t worried about whether the meltdown will alter institutional interest in crypto.

摘要： Sam Bankman-Fried has been arrested by The Royal Bahamas Police Force.

摘要： Fundamental concepts around time series analysis and time series forecasting, including everything from classical approaches to modern machine learning models with examples in Python

摘要： 美國能源部將於13日宣布目前研究中的核融合技術取得重大突破。核融合的原理因近似太陽，長久以來被人們視為具備潔淨、用不盡等特質的終極能源。

摘要： Are you preparing for a Google Data Scientist interview? Congratulations!

摘要： After the industrial revolution, human development accelerated; however, the progress of civilization also caused damage to the environment. The climate anomalies are getting increasingly severe, and the world has started to protect the environment and join the ranks of a friendly environment. However, some enterprises are deceiving the public by doing something “not green” in the name of “green.”