Skip to content

trenton3983/DataCamp

BranchesTags

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

605 Commits
.idea
.idea
 
 
Images
Images
 
 
data
data
 
 
functions
functions
 
 
.gitattributes
.gitattributes
 
 
.gitignore
.gitignore
 
 
2018-08-25_cleaning_data_with_python.ipynb
2018-08-25_cleaning_data_with_python.ipynb
 
 
2019-01-24_pandas_dataframes.ipynb
2019-01-24_pandas_dataframes.ipynb
 
 
2019-02-04_manipulating_dataframes_with_pandas.ipynb
2019-02-04_manipulating_dataframes_with_pandas.ipynb
 
 
2019-02-05_intro_to_python_for_finance.ipynb
2019-02-05_intro_to_python_for_finance.ipynb
 
 
2019-02-12_intro_to_databases_in_python.ipynb
2019-02-12_intro_to_databases_in_python.ipynb
 
 
2019-03-23_merging_dataframes_with_pandas.ipynb
2019-03-23_merging_dataframes_with_pandas.ipynb
 
 
2019-07-10_statistical_thinking_1.ipynb
2019-07-10_statistical_thinking_1.ipynb
 
 
2019-07-19_fraud_detection_python.ipynb
2019-07-19_fraud_detection_python.ipynb
 
 
2019-11-21_joining_data_in_sql.ipynb
2019-11-21_joining_data_in_sql.ipynb
 
 
2019-12-13_intro_to_relational_databases.ipynb
2019-12-13_intro_to_relational_databases.ipynb
 
 
2020-03-05_intro_to_data_visualization_in_python.ipynb
2020-03-05_intro_to_data_visualization_in_python.ipynb
 
 
2020-03-15_interactive_data_visualization_with_bokeh.ipynb
2020-03-15_interactive_data_visualization_with_bokeh.ipynb
 
 
2020-05-21_intro_to_network_analysis_in_python.ipynb
2020-05-21_intro_to_network_analysis_in_python.ipynb
 
 
2020-06-01_statistical_thinking_2.ipynb
2020-06-01_statistical_thinking_2.ipynb
 
 
2020-10-14_supervised_learning_sklearn.ipynb
2020-10-14_supervised_learning_sklearn.ipynb
 
 
2021-03-15_intro_to_shell.ipynb
2021-03-15_intro_to_shell.ipynb
 
 
2021-03-29_unsupervised_learning_in_python.ipynb
2021-03-29_unsupervised_learning_in_python.ipynb
 
 
2021-04-19_intro_to_deep_learning_in_python.ipynb
2021-04-19_intro_to_deep_learning_in_python.ipynb
 
 
2024-01-19_school_budgeting_with_machine_learning_in_python.ipynb
2024-01-19_school_budgeting_with_machine_learning_in_python.ipynb
 
 
2024-01-29_working_with_the_openai_api.ipynb
2024-01-29_working_with_the_openai_api.ipynb
 
 
DataCamp NB Template.ipynb
DataCamp NB Template.ipynb
 
 
Intermediate_Python.py
Intermediate_Python.py
 
 
README.md
README.md
 
 
_config.yml
_config.yml
 
 
a_movie.json
a_movie.json
 
 
case_study_hacker_statistics.py
case_study_hacker_statistics.py
 
 
importing_data_in_python_1.py
importing_data_in_python_1.py
 
 
importing_data_in_python_2.py
importing_data_in_python_2.py
 
 
python_data_science_toolbox_1.py
python_data_science_toolbox_1.py
 
 
python_data_science_toolbox_2.py
python_data_science_toolbox_2.py
 
 
snakes.json
snakes.json
 
 
testing.py
testing.py
 
 
tweets.csv
tweets.csv
 
 
twitter.py
twitter.py
 
 

Repository files navigation

DataCamp

  • DataCamp offers interactive courses in the browser.
    • I've taken coursers from COURSERA, edX, UDACITY, Udemy and LinkedIn Learning, but I prefer the format implemented by DataCamp.
  • As noted, the courses are interactive, in the browser, so I have taken the time to create Jupyter Notebooks for most of the courses I've taken.
    • I have implemented my notebooks in such a way as to be fully executable, though there may be some required backend setup (e.g. downloading data files or setting up a PostgreSQL database).
    • Links to data are in the notebook.
    • There are no hidden functions.
  • An executed HTML version of my notebooks can be found here.

About

code for DataCamp classes

Resources

Readme
Activity

Stars

85 stars

Watchers

5 watching

Forks

95 forks
Report repository

Releases

No releases published

Packages

No packages published

Languages