PKU’s OS on Coursera: Week 12 — Deadlock is an intriguing concept to me. Hope you are also fascinated by it. This article is about conditions for deadlock (mutual exclusion, hold and wait, no preemption, circular waiting), RAG (resource allocation graph), deadlock VS. livelock, deadlock VS. spinlock, methods for handling deadlock, & deadlock prevention. Last article: OS Walkthrough 04— File Management & I/O PKU’s OS on Coursera: Week 09 ~ Week 11yc-kuo.medium.com

PKU’s OS on Coursera: Week 09 ~ Week 11 — The notes I took here were fewer since I was not quite fascinated by the contents over these 3 weeks. This article is about FCB (file control block), abstraction, HDD vs. SSD, file system data structure, block cache, disk scheduling algorithm of HDD [FCFS (first come first serve), SSTF (shortest…

PKU’s OS on Coursera: Week 07 ~ Week 08 — Now we move forward to concepts such as virtual memory, paging, demand paging, segmented paging, TLB (translation lookaside buffer), page fault, page replacement algorithm, Belady anomaly, thrashing, & COW (copy-on-write). Last article: OS Walkthrough 02 — Synchronization PKU’s OS on Coursera: Week 05 ~ Week 06yc-kuo.medium.com Next article: OS Walkthrough 04— File Management & I/O PKU’s OS on Coursera: Week 09 ~ Week 11yc-kuo.medium.com

PKU’s OS on Coursera: Week 05 ~ Week 06 — Here we delve into synchronization approaches ranging from semaphore, monitor, & IPC (interprocess communication); methods ranging from atomic action/primitive, Dekker, Peterson, semaphore, mutex, Hoare monitor, Mesa monitor, spinlock, deadlock VS. starvation, & polling VS. busy waiting. Last article: OS Walkthrough 01— Multi-threading & CPU Scheduling PKU’s OS on Coursera: Week 01 ~ Week 04yc-kuo.medium.com

PKU’s OS on Coursera: Week 01 ~ Week 04 — Operating Systems courses on Coursera are fewer than computer programming, data structure, and algorithm. Though taught in Chinese, Peking University’s Operating Systems render OS basics from a bird’s eye view. After I completed this course, the following passages are the key points I noted encapsulating this OS course. This article…

Utilizing LR, RF, XGBoost with a two-layer stacking — This article is highly simplified. Check the repository on GitHub for complete information. After thorough feature engineering, I leveraged LR, RF & XGBoost, then did a double-layer stacking. Finally, I got 14.83% (17/924) on public leaderboard and 6.82% …

Adding interactions into Random Forest — Check the repository on GitHub for complete details. Top 4 % (833/22219) in Titanic: Machine Learning from Disaster, an iconic entry-level competition on Kaggle, in 2020/05. This project was conducted with R. This was actually an assignment of the graduate level course “Data Science” of department of CS in NCCU…

Approaches besides imputing mean, median or mode — Common ways of dealing with missing values include dropping as well as imputing mean, median or mode. Also, there are advanced approaches like Random Forest & BayesianRidge. Then, how to ensure the best practice of processing missing values avoiding underfitting & overfitting? Outline (1) Prerequisites (2) Two Kinds of Missing Values (3) Methods…

Holt-Winters, SARIMA, auto ARIMA, ACF, PACF & differencing — Keywords: Holt-Winters, Exponential smoothing, SARIMA, Auto ARIMA, Pmdarima, ACF, PACF, Differencing, Seasonal decomposition Complete Python code on Colab: https://bit.ly/371pUN5 We assume the reader is already familiar with time series theories including SARIMA & Holt-Winters; if not, check references [3][5][7][9][13] for more details. Hence, we put emphasis primarily on how to…