Many economic studies discuss the relationship between income and happiness. This is not a formal economics blog, so I will not introduce them. Therefore, the research part will not be too detailed or accurate. I mainly want to talk about my own thoughts. For details of the studies, please see my references.

This year, NVIDIA opened a new metaverse department in Taiwan and is recruiting for various positions, including front-end engineers, and research scientists. I went for an interview for the deep learning engineer position.

In June of last year (2022), I took out a loan to buy stocks. For a while, the unrealized gains and losses were negative, but recently it has been a year and the stock market has performed well, so I would like to share my experience.

I have been a software engineer for nine years. Ten years ago, I still had one year of student life to do things that office workers don’t have much time to do. I’ve taken some detours in the past. If I had myself as a career mentor ten years ago, I would definitely have a more successful career now.

There seem to be many misunderstandings about Leetcode (or algorithm problems), such as the need to memorize all Leetcode problems before going for an interview, or that algorithm problems are intelligence tests (so problem-solving ability cannot be improved through practice). Many people criticize algorithm interviews as being disconnected from work, but we have no control over how each company interviews candidates, and discussing this has no help in passing the interview. Here I want to share…

Talent vs Luck: the role of randomness in success and failure, a 2018 paper that won the 2022 Ig Nobel Prize in Economics.

The productization of ChatGPT has set off another wave of AI fever in the world. This time, unlike AlphaGo, everyone can register for an account to play. In addition to text-generating AI, there is also image-generating AI that produces images that are indistinguishable from human works, and anyone can try it out for free. Even people who don’t know coding can easily use them, which will definitely affect the work of machine learning engineers, but I think machine learning engineers can…

The year 2021 was a cryptocurrency boom, with a market cap of $2.9 trillion, which was pretty amazing. Now, with only about a trillion market cap left, it’s a good time to slow down and think about investing without fear of missing out.

In the second half of 2021, I interviewed with Amazon and Microsoft, but unfortunately was rejected after virtual onsite interviews. The positions I applied for were software engineer in machine learning. Here I would like to share my interview experience and preparation methods.

I have 6 years working experience as a machine learning engineer (though job title not exact “machine learning engineer”, but the responsibility is), started this role before the deep learning boom. My job is translate business problems into machine learning solvable problems and productionize the models with backend engineers. Sometimes, I also need to develop the data pipeline. I will share about the math that machine learning engineers need in this article.