Meta-learning is an exciting trend of research in the machine-learning community which tackles the problem of learning to learn.

Recently, AI systems have mastered a range of video-games such as Atari classics Breakout and Pong.  But as impressive as this performance is, AI still relies on the equivalent of thousands of hours of gameplay to reach and surpass the performance of human…

Explore XGBoost parameters and hyperparameter tuning like learning rate, depth of trees, regularization, etc. to improve model accuracy.

这是正经的前端频道

Numerical optimization is at the core of much of machine learning. In this post, we derive the L-BFGS algorithm, commonly used in batch machine learning applications.

Since writing this post back in 2018, I have extended this to a 4-part series on
causal inference:

* ➡️️ Part 1: Intro to causal inference and do-calculus
[https://www.inference.vc/untitled]
* Part 2: Illustrating Interventions with a Toy Example
…

A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks - GitHub - IntelLabs/nlp-architect: A model library...

This post is actually about artificial intelligence, and argues a position that many AI researchers will disagree with. Specifically, it arg...

I was recently asked if machine learning requires evaluation metrics. The answer is no, and the fact that people are asking such questions suggests that some newcomers to the field may have a limit…

Why do some English plurals end in "en" instead of "s"?

There are roughly four types of loss functions that are used in NLP research. The real loss function given to us by the world. Typically i...

Module description for 7AAN2059 Philosophy of Language

Collect and catagorize the online graphic design references, materials, thoughts, inspiration and so on.