| Date |
Summary |
| 2022.3.30 |
- Syllabus: grading policy, algorithm, working environment
- Data, data type, and vectorization
- Variables and data types (integers, floats, strings)
- Numerical errors: finite precision
- Assignment operator (=) with a simplified memory model
- Arithmetic operators (+, −, *, /, ^)
- Numeric arrays and cell arrays
- Market data of Taiwan Stock Exchange (from TEJ)
|
| 2022.4.6 |
- Data, data type, and vectorization (cont'd)
- Strings and dates
- Vectorization: element-by-element operations
- Relational operators (<, ==, >) and logical values (true/false)
- Logical operators (~, &, |) and quantifiers (all, any)
- (FYR) Live script
- Flow controls
- Selections (&&, ||, if-elseif-else, switch-case-otherwise)
- Loops (for, while) (also try this game)
- Numerical example: Monte Carlo simulation
|
| 2022.4.9 |
- Flow controls (cont'd)
- Numerical example: bisection method for root-finding
- Jump statements (break, continue)
- Nested loops
- Two common algorithms: sorting and random permutation
- Performance analysis
|
| 2022.4.13 |
- Plotting
- 2D charts: line, bar, dual y-axis chart, histogram, stackedplot (feat. table), candle plot (feat. timetable), fplot, error bar, pie, word cloud, subplot, quiver, contour, worldmap & geoshow (see tw_map.pdf)
- 3D charts: mesh, surface, 3d line
- Cool example 1: GPS-TEC 的資料取得、轉換，並繪製變化圖, 2018
- Cool example 2: Visualization, 2019
- Application: k-means clustering (code: kmeans_demo.m, kmeans_demo2.m)
|
| 2022.4.16 |
No class due to personal excuse.
|
| 2022.4.20 |
- Functions
- User-defined functions
- Call stack and variable scope
- Debugger
- Primary function with helper functions
- Function handle and anonymous function
- Error and error handling (try-catch)
- Exercise: problem set
- Special issue: text processing
- Special issue: file operations & other I/O
- Spreadsheets: excel, csv
- File operations
- Mat file
- Example: data pooling
|
| 2022.4.23 |
- Matrix computation
- Vectors and matrices
- Inner product: projection
- Linear transform: basic concepts of linear algebra (vector space, linear independece, span, basis, dimension)
|
| 2022.4.27 |
- Matrix computation (cont'd)
|
| 2022.4.30 |
|
| 2022.5.4 |
- Special issue: Simulink tutorial (try Simulink examples)
- Special issue: machine learning (read machine learning and big data investing white paper and mastering machine learning: a step-by-step guide with MATLAB)
- Special issue: deep learning toolbox (deep_learning_demo.m)
- (FYR) Courses of machine learning: Hsuan-Tien Lin and 李宏毅
- Statistics
- Introduction to Data Science: we will follow some materials from there.
- Basic concepts: probability distribution, random variable, simple random sampling, statistic, estimator, hypothesis
- Descriptive statistics: mean, median, mode, var, std, movmean, movstd
- Cumulative probability function (cdf) & probability density function (pdf): uniform, normal (normcdf, normpdf), chi-square (chi2cdf, chi2pdf)
- Point estimation & the &100 - alpha;-% confidence interval
- Hypothesis testing & Type I/II error:
- The z test (ztest)
- The χ² goodness-of-fit test (chi2gof)
- The t test (ttest)
- The F test (vartest2)
- Normality test
- Jarque–Bera test (jbtest)
- Kolmogorov–Smirnov test (kstest)
- Analysis of variance (ANOVA)
- One-way ANOVA (anova1)
- Two-way ANOVA (anova2)
- Correlation (cov, corr, corrcoef): Bivariate_Histogram_Plot.zip, Heatmap_Chart.zip
- Multiple linear regression (regress, fitlm)
- Option pricing: EuropeanCallPrice_MC.pdf (Ito_calculus.pdf)
|
| 2022.5.7 |
- Demonstration of final projects
|