Tzu-Chi Lin[The Effective Engineer 筆記] Invest in Iteration Speed這篇是 Execute 底下的第一章,說明迭代(iteration)速度的重要性。迭代指的是,code 從 commit 到 deploy to production 的過程,更廣義的迭代可以說,從有 idea 到 idea in production…Feb 6, 2021Feb 6, 2021
Tzu-Chi Lin[The Effective Engineer 筆記] Prioritize Regularly這是 Adopt the right mindset 下的第三章,也是這部分的最後一章,prioritize regularly,隨時對你要做的事情排序。如同前面提到的,時間是最寶貴、且有限的資源,我們要如何排序、先做high leverage 的事便是一件重要的事Jan 31, 2021Jan 31, 2021
Tzu-Chi Lin[The Effective Engineer 筆記] Optimize for Learning這是 Adopt the right mindset 下的第二章,最佳化學習,可以把它想成,如何提高學習的 leverage 並持續學習。作者認為,世界上有兩種人,一種為 fixed…Jan 31, 2021Jan 31, 2021
Tzu-Chi Lin[The Effective Engineer 筆記] Focus on High-Leverage Activities這是 Adopt the right mindset 下的第一章,也是整本書的核心概念:隨時專注在 high leverage 的活動。所以什麼是 leverage 呢? leverage (n.) 槓桿作用、利用。嗯好像還是完全不懂,讓我們來看看作者的定義Jan 19, 2021Jan 19, 2021
Tzu-Chi LinThe Effective Engineer 筆記如同書名,本書在介紹如何成為有效率的工程師。作者提出了一套架構(framework)和具體的說明,讓讀者可以按部就班的練習,也為每個重點提供了現實生活中的例子Jan 19, 2021Jan 19, 2021
Tzu-Chi Linin30 days of Machine LearningDay 6 — Naive Bayes ClassifierToday we’ll learn a basic classifier based on probability, naive bayes classifier. We start from Bayes theorem. And we’ll see two examples…Dec 23, 20181Dec 23, 20181
Tzu-Chi Linin30 days of Machine LearningDay 5 -Entropy, Relative Entropy, and Cross EntropyToday we’ll focus on the theory of entropy. Understand the intuition of entropy, and how it relates to logistic regression. We’ll cover…Dec 21, 2018Dec 21, 2018
Tzu-Chi Linin30 days of Machine LearningDay 4 — Logistic RegressionToday we’ll focus on a simple classification model, logistic regression. From its intuition, theory, and of course, implement it by our…Dec 7, 20181Dec 7, 20181
Tzu-Chi Linin30 days of Machine LearningDay 3 — K-Nearest Neighbors and Bias–Variance TradeoffToday we’ll learn our first classification model, KNN, and discuss the concept of bias-variance tradeoff and cross-validation. Also, we…Dec 4, 20185Dec 4, 20185
Tzu-Chi Linin30 days of Machine LearningDay 2 — Supervised Learning and Linear RegressionToday we’ll walk through supervised learning, and spend most of the time on linear regression, especially gradient descent algorithm…Nov 20, 2018Nov 20, 2018