Notebook 2019

A collection of coursework, study notes, and programming exercises from 2019, covering bioinformatics, machine learning, and statistical computing.

Repository Structure

.
├── Notes/                          # Standalone study guides and tutorials
│   ├── Bioinformatics_Introduction.md
│   ├── GitHub_Usage.md
│   └── Jupyter_Installation.md
├── Homework/                       # University coursework assignments
│   ├── Bioinformatics_CAU/         # Sequence alignment with BLOSUM62 scoring
│   ├── C_CAU/                      # C programming exercises by topic
│   ├── Python_CAU/                 # Python basics practice problems
│   ├── Python_PKU/                 # Web crawler + word cloud project
│   └── R_CAU/                      # R statistics lab notes
├── Python/                         # Self-study Python projects
│   ├── MachineLearning_Ng/         # Andrew Ng ML course notes & exercises
│   ├── PythonCrawler_Douban/       # Douban Top250 movie data crawler
│   └── PythonFromStatistician_Book/ # Book notes: NumPy, Pandas, Matplotlib, SciPy
├── R/                              # Self-study R projects
│   └── Examples_CAU/               # R programming course examples
├── .gitignore
├── LICENSE                         # MIT License
└── README.md

Homework

Folder	Course	Description
Bioinformatics_CAU/	Bioinformatics (CAU)	Python implementation of sequence alignment with BLOSUM62 scoring matrix backtracking. Includes a STAR aligner configuration file (mapping.gtex).
C_CAU/	C Programming (CAU)	Basic C exercises organized by topic: input/output, sequential/loop/array structures, and functions.
Python_CAU/	Python Basics (CAU)	Fundamentals: string manipulation, palindrome detection, Hanoi towers, prime numbers, and more.
Python_PKU/	Python (PKU)	Web crawler fetching Sohu News articles, with Chinese word segmentation (jieba) and word cloud visualization.
R_CAU/	R Statistics (CAU)	Lab notes covering ANOVA, multicollinearity, linear regression, cluster analysis, and ggplot2.

Python

Folder	Description
MachineLearning_Ng/	Notes from Andrew Ng's Machine Learning course. Covers algorithm fundamentals, mathematical derivations (with LaTeX), and Python implementations of exercises (linear/logistic regression, neural networks).
PythonCrawler_Douban/	Jupyter notebook implementing a static web crawler using Requests + BeautifulSoup to scrape Douban Top250 movie data.
PythonFromStatistician_Book/	Study notes from Python: A Statistician's Perspective by Wu Xizhi. Covers NumPy, Pandas, Matplotlib, SciPy, basic data processing, and hypothesis testing.

R

Folder	Description
Examples_CAU/	Code examples from the R Programming course at CAU. Topics include dplyr, tidyr, stringr, purrr, ggplot2 (facets, colors, points, boxplots, bar charts, histograms), cowplot, rvest web scraping, GIS with leaflet, formattable, and Monty Hall simulation.

Notes

File	Description
Bioinformatics_Introduction.md	Introduction to sequencing platforms (Illumina, Roche 454, SOLiD, PacBio, Ion), genome assembly tools (SSAKE, Edena, SOAPdenovo), and ChIP-seq data analysis.
GitHub_Usage.md	Git and GitHub tutorial notes covering SSH setup, branching, merging, rebasing, remote operations, issues, and pull requests.
Jupyter_Installation.md	Step-by-step Jupyter Notebook installation guide for both Windows (Anaconda) and Linux (remote server with remote access).

License

This project is licensed under the MIT License — see the LICENSE file for details.