MTH 448/548
Logistics
MTH 448/548 Syllabus
Current Tasks
Project Report Guide
Useful links
Schedule
Preliminaries
Week 1 (1/31-2/6)
Week 2 (2/7-2/13)
Week 3 (2/14-2/20)
Week 4 (2/21-2/27)
Week 5 (2/28-3/6)
Week 6 (3/7-3/13)
Week 7 (3/14-3/20)
Week 8 (3/28-4/3)
Week 9 (4/4-4/10)
Week 10 (4/11-4/17)
Week 11 (4/18-4/24)
Week 12 (4/25-5/1)
Week 13 (5/2-5/8)
Week 14 (5/9-5/15)
Tools
Numpy
Pandas
Seaborn
Plotly
Requests
Beautiful Soup
JSON
Regular expressions
SQL
Projects
Project: Recognizing digits with k-NN
Project: MNIST with k-means
Project: Baby names
Project: Scrapping marathon results
Project: Discord logs
Project: Analysis of marathon results
Project: Text classification with naive Bayes
Optional Project: Music database
MTH 448/548
MTH 448/548
»
MTH 448/548 Data Oriented Computing
MTH 448/548 Data Oriented Computing
¶
Logistics
MTH 448/548 Syllabus
Class meetings
Instructor
Prerequisites
Learning Outcomes
Course Resources
Grading
Project Reports
Weekly digests
Incomplete Grades
Academic Integrity
Accessibility Resources
Current Tasks
Weekly Digest 13
Project Report Guide
Collaboration
Using external resources
Report grading rubrics
Report Style Guide
Report introduction
Report conclusions
Report organization
References
Math formatting
Code structure
Code sequencing
Code comments
Execution errors
Output size
Output formatting
Graphs and plots
Notebook gallery
Useful links
Markdown cheatsheet
LaTeX symbols
Python docs
Numpy docs
Seaborn docs
Plotly docs
Json docs
Pandas docs
Requests docs
Beautiful Soup docs
Python Data Science Handbook by Jake VanderPlas
Schedule
Preliminaries
Week 1 (1/31-2/6)
Week 2 (2/7-2/13)
Week 3 (2/14-2/20)
Week 4 (2/21-2/27)
Week 5 (2/28-3/6)
Week 6 (3/7-3/13)
Week 7 (3/14-3/20)
Week 8 (3/28-4/3)
Week 9 (4/4-4/10)
Week 10 (4/11-4/17)
Week 11 (4/18-4/24)
Week 12 (4/25-5/1)
Week 13 (5/2-5/8)
Week 14 (5/9-5/15)
Tools
Numpy
Numpy Basics
Vectorized computations
Numpy arrays vs lists
Creating numpy arrays
Multidimensional numpy arrays
Mathematical operations on multidimensional arrays
Slicing multidimensional arrays
Sorting
Aggregation functions
Boolean and fancy indexing
Boolean arrays
Logical operations on Boolean arrays
Indexing with Boolean arrays
Fancy indexing
Fancy indexing example
Array shapes and broadcasting
Shapes of numpy arrays
Broadcasting
Broadcasting rules
Pandas
Pandas basics
Pandas Series
Pandas DataFrame
Selecting data in a DataFrame
Sorting
Modifying DataFrames and Series
Aggregations
Reshaping DataFrames
Transpose
Setting and reseting an index
MultiIndex
Stack and unstack
GroupBy
The GroupBy object
Simple aggregations
GroupBy.agg
GroupBy.transform
GroupBy.apply
groupby options
Combining DataFrames
pd.concat
pd.merge
Seaborn
Seaborn
Plots from dataframes
Figure-level and axes-level functions
Customizing plots
Seaborn plot types
Scatter plot
Line plot
Bar plot
Strip plot
Swarm plot
Box plot
Violin plot
Histogram plot
Joint plot
Pair plot
Plotly
Plotly basics
Traces and figures
Figure layout
Underscore Notation
Updating layout
Updating traces
Subplots
Templates
Plotly Express
Plots from dataframes
Customizing plots
Plotly Express plot types
Scatter plot
Line plot
Bar plot
Strip plot
Box plot
Violin plot
Histogram plot
Sunburst plot
Marginal plots
Pair plot
Animated plots
Choropleth maps
Requests
Requests basics
Binary files
User-Agent
Sending data
POST requests
Beautiful Soup
First steps
Links
Link formats
Images
Tables
JSON
The json module
Example: currency exchange rates
Regular expressions
Regular expressions
Prelude: raw strings
Visualizing regular expressions
Character classes
Repetitions
Non-greedy matches
Match groups
Anchors
Flags
Inserting comments
Matching special characters
Functions in the re module
re.findall
re.sub
SQL
SQL basics
SQL in Jupyter Notebook
Creating tables
Deleting tables
Creating table records
Modifying records
Deleting records
SQL queries
SELECT … FROM …
WHERE
ORDER
LIMIT
Aggregate functions
GROUP BY
HAVING
SQL joins, union, intersection
INTERSECT
UNION
EXCEPT
Joins
Views
SQL with Python
Projects
Project: Recognizing digits with k-NN
MNIST database
Objectives
Project: MNIST with k-means
Objectives
Project: Baby names
Database of baby names
Objectives
Project: Scrapping marathon results
Objectives
Notes
Project: Discord logs
Objectives
Part 1
Part 2
Note
Project: Analysis of marathon results
Objectives
Project: Text classification with naive Bayes
Objectives
Optional Project: Music database
Objectives
Notes.
Exercise 1
Exercise 2
Exercise 3
Exercise 4
Exercise 5
Exercise 6
Exercise 7
Exercise 8
Exercise 9
Exercise 10