Achieve the optimal ML model in an automated and smart way — Table of contents Introduction Hyperparameters and scikit-learn Tunning Methods Tunning Hyperparameters with Optuna Conclusion Introduction I recently finished my first machine learning project on Kaggle, predicting sale price with the Boston Housing dataset (co-author: Julia Yang). Please find our work, which achieved top 9% among 5k competitors, at [Top 9%] House Price.

Recently, I’m working on creating a MySQL RDS instance with CloudFormation template. Although there have been tons of documents from both AWS officials or the community talking about this, I feel there are not many documents diving deep about making MasterUserPassword secure. When creating a MySQL instance, RDS will create…

If you’re not familiar with AWS Step Functions, it is a service where we can create state-machines to orchestrate asynchronous tasks in workflows without worrying too much about any underlying infrastructure and operations. …

I’ve been using the Java library dnsjava(org.xbill.DNS) a lot recently to make DNS queries. Since my work will rely on the behavior of that library, I figured I have to understand it better. …

In Go, append(slice, x) is one of the most used built-in functions. But have you ever thought about a simple question: what is the time complexity of it? The short answer: The amortized cost of append() is O(1), but the worst-case cost is O(N). Before I move to the long…

Let’s start directly with an example (go playground): package main import "fmt" func main() { var a interface{} fmt.Printf("a == nil is %t\n", a == nil) var b interface{} var p *int = nil b = p fmt.Printf("b == nil is %t\n", b == nil) } What is your expectation…