Introduction to Numerical Analysis (2019)
Kai-Feng
Chen
National
Taiwan
University
Date:
2019/Feb to 2019/June
Location: classroom R112, New Physics Building, NTU
We will introduce commonly used numerical methods in
scientific computing in this lecture. The base computing language
will be Python.
Part I: Introduction to Python (slides only)
The basis / Control flow / Types and data
structure /
Functions and modules /
Input & Output / Classes
and others
Part II: Numerical analysis basis
Error analysis / Numerical differential and integration /
Random numbers / Linear algebra / Root finding and minimum
finding / Differential equations / Visualization
Part III: Advanced topics
Machine
learning /
Data modeling and fitting / Statistical analysis
Materials used in 2018 are available HERE.
Lecture
0-1: All you need to know about this course
Slides: lecture-001.pdf
Lecture
1-1: Introduction to Python
Slides: lecture-101.pdf
Lecture
1-2: Control flow
Slides: lecture-102.pdf
Lecture 1-3: Functions and modules
Slides:
lecture-103.pdf
Lecture 1-4: More on sequence types & data structures
Slides:
lecture-104.pdf
Lecture 1-5: I/O, exceptions and class
Slides:
lecture-105.pdf
Lecture 2-1: The Art of Numerical Analysis
Slides:
lecture-201.pdf
Materials:
wav_ana.py / test2.wav
/ test1.wav / l201-example-01.py
/ l201-example-02.py / l201-example-02a.py
Lecture 2-2: Numerical Differential & Integration
Slides:
lecture-202.pdf
Materials:
l202-example-01.py / l202-example-01a.py
/ l202-example-01b.py /
l202-example-02.py /
l202-example-02a.py / l202-example-03.py
/ l202-example-04.py / l202-example-05.py
/ l202-example-05a.py
/ l202-example-06.py
Lecture 2-3: NumPy array & linear algebra (I)
Slides:
lecture-203.pdf
Materials:
l203-example-01.py / l203-example-02.py
/ l203-example-03.py / l203-example-04.py
/
l203-example-05.py / l203-example-06.py
/ l203-example-07.py / l203-example-08.py
/
l203-example-08a.py
/ l203-example-09.py
Lecture 2-4: NumPy array & linear algebra (II)
Slides:
lecture-204.pdf
Materials:
l204-example-01.py / l204-example-02.py
/ l204-example-02a.py /
l204-example-03.py /
l204-example-04.py / l204-example-04a.py
/ l204-example-05.py / l204-example-06.py
/
l204-example-07.py / l204-example-08.py
/ l204-example-09.py / l204-example-09a.py
/
l204-example-09b.py / testimage.jpg
Lecture 2-5: Root finding & minimization
Slides:
lecture-205.pdf
Materials:
l205-example-01.py / l205-example-02.py
/ l205-example-02a.py /
l205-example-03.py /
l205-example-03a.py / l205-example-04.py
/ l205-example-05.py / l205-example-06.py
/
l205-example-07.py / l205-example-08.py
/ l205-example-08a.py /
l205-example-09.py /
l205-example-10.py / l205-example-10a.py
/ l205-example-10b.py /
l205-practice-02.py
Lecture 2-6: Solving ordinary differential equations
Slides:
lecture-206.pdf
Materials:
l206-example-01.py / l206-example-02.py
/ l206-example-03.py /
l206-example-03a.py /
l206-example-04.py
/ l206-example-04a.py
/ l206-example-05.py
/ l206-example-06.py /
l206-example-07.py / l206-example-07a.py
/ l206-example-07b.py /
l206-example-08.py /
l206-example-08a.py / l206-example-08b.py
/l206-example-09.py / l206-example-09a.py
/
l206-example-09b.py / l206-example-10.py
/ l206-example-10a.py /
l206-practice-01-template.py
/ l206-practice-02-template.py
Lecture 2-7: Random numbers
Slides:
lecture-207.pdf
Materials:
l207-example-01.py / l207-example-01a.py
/ l207-example-01b.py /
l207-example-02.py /
l207-example-03.py / l207-example-04.py
/ l207-example-05.py / l207-example-06.py
/
l207-example-06a.py / l207-example-06b.py
/ l207-example-07.py / l207-example-07a.py
/
l207-example-08.py / l207-example-08a.py
/ l207-example-09.py
Tournament
Slides:
tournament.pdf
Materials:
tournament.py / player_template.py
Lecture 3-1: Brief on machine learning
Slides:
lecture-301.pdf
Materials:
mnist.npz / l301practice.npz
/
l301-example-01.py / l301-example-01a.py
/ l301-example-01b.py /
l301-example-02.py /
l301-example-02a.py / l301-example-02b.py
/ l301-example-02c.py /
l301-example-03.py /
l301-example-03a.py / l301-example-03b.py
/ l301-example-04.py / l301-example-04a.py
/
l301-example-04b.py / l301-example-05.py
/ l301-example-05a.py /
l301-example-06.py /
l301-example-07.py / l301-example-07a.py
/ l301-example-07b.py
Lecture 3-2: Incorporating Nonlinear Models
Slides:
lecture-302.pdf
Materials:
neurons.py
l302-example-01.py / l302-example-02.py
/ l302-example-02a.py /
l302-example-03.py /
l302-example-04.py / l302-example-04a.py
/ l302-example-05.py / l302-example-05a.py
/
l302-example-05b.py / l302-example-06.py
Lecture 3-3: Tricks for Improving Neural Network
Slides:
lecture-303.pdf
Materials:
l303-example-01.py / l303-example-02.py
/ l303-example-02a.py /
l303-example-03.py /
l303-example-04.py / l303-example-04a.py
/ l303-example-04b.py /
l303-example-04c.py /
l303-example-05.py / l303-example-06.py
/ l303-example-06a.py /
l303-example-06b.py /
l303-example-06c.py / l303-example-06d.py
/ l303-example-07.py / l303-example-07a.py
Lecture 3-4: Deep Structured Learning
Slides:
lecture-304.pdf
Materials:
l304-example-01.py / l304-example-01a.py
/ l304-example-01b.py /
l304-example-02.py /
l304-example-03.py / l304-example-04.py
/ l304-example-04a.py /
l304-example-05.py
/
l304-example-05a.py / l304-example-06.py
/ l304-example-07.py / l304-example-08.py
/
midi_phraser.py
/ rnn_files.zip / font_data.npy
/ l304practice.npz
Lecture 3-5: Modeling of Data – Probability & Probability Distributions
Slides:
lecture-305.pdf
Materials:
l305-example-01.py / l305-example-02.py
/ l305-example-03.py
Lecture 3-6: Modeling of Data – Parameter Estimation
Slides:
lecture-306.pdf
Materials:
l306-example-01.py / l306-example-02.py
/ l306-example-02a.py /
l306-example-03.py /
l306-example-03a.py / l306-example-03b.py
/ l306-example-04.py / l306-example-04a.py
/
l306-example-04b.py / l306-example-04c.py
/ l306-example-05.py / l306-example-05a.py
/
l306-example-06.py / l306-example-06a.py
/
dimuon.npy
/ clean_data.npy