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If you have not done already you need to install Anaconda first.

Install the Dependencies

The notebooks are compatible with Python version 3.5 or later, all packages required are listed in environment.yml and requirements.txt. Pick any option below to install the dependencies:

Create a conda environment

Open your Terminal (or Command Prompt on Windows).

Use environment.yml to create a conda environment by executing the following command line:

conda env create -f environment.yml

This creates a conda environment named "mcfds_LinAlg". For conda 4.6 and later versions, activate this environment with

conda activate mcfds_LinAlg

For conda version prior to 4.6, run source activate mcfds_LinAlg on Linux and MacOS, activate mcfds_LinAlg on Windows.

Install with conda

conda install matplotlib numpy scipy jupyter imageio ipywidgets

Install with pip

Install the packages using requirements.txt for pip:

pip install -r requirements.txt

Check Installation

Run the script check_install.py to check whether the required packages are installed correctly:

python check_install.py

Opening and running Jupyter Notebooks

To launch a Jupyter notebook, open your terminal and navigate to the directory where you would like to save your notebook. Then type the command jupyter notebook in the your terminal (at the directory where you have saved your notebook) and the program will instantiate a local server at localhost:8888 (or another specified port). For more detailed tutorial see here: https://www.codecademy.com/article/how-to-use-jupyter-notebooks

You can also run a Jupyter notebook via VSCode. Here is the full guide: https://code.visualstudio.com/docs/datascience/jupyter-notebooks

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readme.md
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requirements.txt
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Repository files navigation
If you have not done already you need to install Anaconda first.
Install the Dependencies
The notebooks are compatible with Python version 3.5 or later, all packages required are listed in environment.yml and requirements.txt. Pick any option below to install the dependencies:
Create a conda environment
Open your Terminal (or Command Prompt on Windows).
Use environment.yml to create a conda environment by executing the following command line:
conda env create -f environment.yml

This creates a conda environment named "mcfds_LinAlg". For conda 4.6 and later versions, activate this environment with
conda activate mcfds_LinAlg

For conda version prior to 4.6, run source activate mcfds_LinAlg on Linux and MacOS, activate mcfds_LinAlg on Windows.
Install with conda
conda install matplotlib numpy scipy jupyter imageio ipywidgets

Install with pip
Install the packages using requirements.txt for pip:
pip install -r requirements.txt

Check Installation
Run the script check_install.py to check whether the required packages are installed correctly:
python check_install.py

Opening and running Jupyter Notebooks
To launch a Jupyter notebook, open your terminal and navigate to the directory where you would like to save your notebook. Then type the command jupyter notebook in the your terminal (at the directory where you have saved your notebook) and the program will instantiate a local server at localhost:8888 (or another specified port). For more detailed tutorial see here: https://www.codecademy.com/article/how-to-use-jupyter-notebooks
You can also run a Jupyter notebook via VSCode. Here is the full guide: https://code.visualstudio.com/docs/datascience/jupyter-notebooks
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Mapper.ipynb
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Persistent_Homology.ipynb
Topological_data_analysis_final.pdf
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eckart-young.ipynb
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environment.yml
environment.yml
hw1.ipynb
hw1.ipynb
hw2.ipynb
hw2.ipynb
hw2_soln.ipynb
hw2_soln.ipynb
hw3.ipynb
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hw4.ipynb
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markov-chain.png
markov-chain.png
matrix_basics.ipynb
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notes_on_perpendicular_least_squares_and_svd.pdf
notes_on_perpendicular_least_squares_and_svd.pdf
pca.ipynb
pca.ipynb
plot_helper.py
plot_helper.py
readme.md
readme.md
requirements.txt
requirements.txt
svd-example.ipynb
svd-example.ipynb
Repository files navigation
If you have not done already you need to install Anaconda first.
Install the Dependencies
The notebooks are compatible with Python version 3.5 or later, all packages required are listed in environment.yml and requirements.txt. Pick any option below to install the dependencies:
Create a conda environment
Open your Terminal (or Command Prompt on Windows).
Use environment.yml to create a conda environment by executing the following command line:
conda env create -f environment.yml

This creates a conda environment named "mcfds_LinAlg". For conda 4.6 and later versions, activate this environment with
conda activate mcfds_LinAlg

For conda version prior to 4.6, run source activate mcfds_LinAlg on Linux and MacOS, activate mcfds_LinAlg on Windows.
Install with conda
conda install matplotlib numpy scipy jupyter imageio ipywidgets

Install with pip
Install the packages using requirements.txt for pip:
pip install -r requirements.txt

Check Installation
Run the script check_install.py to check whether the required packages are installed correctly:
python check_install.py

Opening and running Jupyter Notebooks
To launch a Jupyter notebook, open your terminal and navigate to the directory where you would like to save your notebook. Then type the command jupyter notebook in the your terminal (at the directory where you have saved your notebook) and the program will instantiate a local server at localhost:8888 (or another specified port). For more detailed tutorial see here: https://www.codecademy.com/article/how-to-use-jupyter-notebooks
You can also run a Jupyter notebook via VSCode. Here is the full guide: https://code.visualstudio.com/docs/datascience/jupyter-notebooks
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eckart-young.ipynb
environment.yml
environment.yml
hw1.ipynb
hw1.ipynb
hw2.ipynb
hw2.ipynb
hw2_soln.ipynb
hw2_soln.ipynb
hw3.ipynb
hw3.ipynb
hw4.ipynb
hw4.ipynb
make-up-corrected.pdf
make-up-corrected.pdf
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make-up.pdf
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markov-chain.png
matrix_basics.ipynb
matrix_basics.ipynb
notes_on_perpendicular_least_squares_and_svd.pdf
notes_on_perpendicular_least_squares_and_svd.pdf
pca.ipynb
pca.ipynb
plot_helper.py
plot_helper.py
readme.md
readme.md
requirements.txt
requirements.txt
svd-example.ipynb
svd-example.ipynb
Repository files navigation
If you have not done already you need to install Anaconda first.
Install the Dependencies
The notebooks are compatible with Python version 3.5 or later, all packages required are listed in environment.yml and requirements.txt. Pick any option below to install the dependencies:
Create a conda environment
Open your Terminal (or Command Prompt on Windows).
Use environment.yml to create a conda environment by executing the following command line:
conda env create -f environment.yml

This creates a conda environment named "mcfds_LinAlg". For conda 4.6 and later versions, activate this environment with
conda activate mcfds_LinAlg

For conda version prior to 4.6, run source activate mcfds_LinAlg on Linux and MacOS, activate mcfds_LinAlg on Windows.
Install with conda
conda install matplotlib numpy scipy jupyter imageio ipywidgets

Install with pip
Install the packages using requirements.txt for pip:
pip install -r requirements.txt

Check Installation
Run the script check_install.py to check whether the required packages are installed correctly:
python check_install.py

Opening and running Jupyter Notebooks
To launch a Jupyter notebook, open your terminal and navigate to the directory where you would like to save your notebook. Then type the command jupyter notebook in the your terminal (at the directory where you have saved your notebook) and the program will instantiate a local server at localhost:8888 (or another specified port). For more detailed tutorial see here: https://www.codecademy.com/article/how-to-use-jupyter-notebooks
You can also run a Jupyter notebook via VSCode. Here is the full guide: https://code.visualstudio.com/docs/datascience/jupyter-notebooks
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Mapper.ipynb
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Persistent_Homology.ipynb
Persistent_Homology.ipynb
Topological_data_analysis_final.pdf
Topological_data_analysis_final.pdf
eckart-young.ipynb
eckart-young.ipynb
environment.yml
environment.yml
hw1.ipynb
hw1.ipynb
hw2.ipynb
hw2.ipynb
hw2_soln.ipynb
hw2_soln.ipynb
hw3.ipynb
hw3.ipynb
hw4.ipynb
hw4.ipynb
make-up-corrected.pdf
make-up-corrected.pdf
make-up.pdf
make-up.pdf
markov-chain.png
markov-chain.png
matrix_basics.ipynb
matrix_basics.ipynb
notes_on_perpendicular_least_squares_and_svd.pdf
notes_on_perpendicular_least_squares_and_svd.pdf
pca.ipynb
pca.ipynb
plot_helper.py
plot_helper.py
readme.md
readme.md
requirements.txt
requirements.txt
svd-example.ipynb
svd-example.ipynb
Repository files navigation
If you have not done already you need to install Anaconda first.
Install the Dependencies
The notebooks are compatible with Python version 3.5 or later, all packages required are listed in environment.yml and requirements.txt. Pick any option below to install the dependencies:
Create a conda environment
Open your Terminal (or Command Prompt on Windows).
Use environment.yml to create a conda environment by executing the following command line:
conda env create -f environment.yml

This creates a conda environment named "mcfds_LinAlg". For conda 4.6 and later versions, activate this environment with
conda activate mcfds_LinAlg

For conda version prior to 4.6, run source activate mcfds_LinAlg on Linux and MacOS, activate mcfds_LinAlg on Windows.
Install with conda
conda install matplotlib numpy scipy jupyter imageio ipywidgets

Install with pip
Install the packages using requirements.txt for pip:
pip install -r requirements.txt

Check Installation
Run the script check_install.py to check whether the required packages are installed correctly:
python check_install.py

Opening and running Jupyter Notebooks
To launch a Jupyter notebook, open your terminal and navigate to the directory where you would like to save your notebook. Then type the command jupyter notebook in the your terminal (at the directory where you have saved your notebook) and the program will instantiate a local server at localhost:8888 (or another specified port). For more detailed tutorial see here: https://www.codecademy.com/article/how-to-use-jupyter-notebooks
You can also run a Jupyter notebook via VSCode. Here is the full guide: https://code.visualstudio.com/docs/datascience/jupyter-notebooks
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Mapper.ipynb
Mapper.ipynb
Persistent_Homology.ipynb
Persistent_Homology.ipynb
Topological_data_analysis_final.pdf
Topological_data_analysis_final.pdf
eckart-young.ipynb
eckart-young.ipynb
environment.yml
environment.yml
hw1.ipynb
hw1.ipynb
hw2.ipynb
hw2.ipynb
hw2_soln.ipynb
hw2_soln.ipynb
hw3.ipynb
hw3.ipynb
hw4.ipynb
hw4.ipynb
make-up-corrected.pdf
make-up-corrected.pdf
make-up.pdf
make-up.pdf
markov-chain.png
markov-chain.png
matrix_basics.ipynb
matrix_basics.ipynb
notes_on_perpendicular_least_squares_and_svd.pdf
notes_on_perpendicular_least_squares_and_svd.pdf
pca.ipynb
pca.ipynb
plot_helper.py
plot_helper.py
readme.md
readme.md
requirements.txt
requirements.txt
svd-example.ipynb
svd-example.ipynb
Repository files navigation
If you have not done already you need to install Anaconda first.
Install the Dependencies
The notebooks are compatible with Python version 3.5 or later, all packages required are listed in environment.yml and requirements.txt. Pick any option below to install the dependencies:
Create a conda environment
Open your Terminal (or Command Prompt on Windows).
Use environment.yml to create a conda environment by executing the following command line:
conda env create -f environment.yml

This creates a conda environment named "mcfds_LinAlg". For conda 4.6 and later versions, activate this environment with
conda activate mcfds_LinAlg

For conda version prior to 4.6, run source activate mcfds_LinAlg on Linux and MacOS, activate mcfds_LinAlg on Windows.
Install with conda
conda install matplotlib numpy scipy jupyter imageio ipywidgets

Install with pip
Install the packages using requirements.txt for pip:
pip install -r requirements.txt

Check Installation
Run the script check_install.py to check whether the required packages are installed correctly:
python check_install.py

Opening and running Jupyter Notebooks
To launch a Jupyter notebook, open your terminal and navigate to the directory where you would like to save your notebook. Then type the command jupyter notebook in the your terminal (at the directory where you have saved your notebook) and the program will instantiate a local server at localhost:8888 (or another specified port). For more detailed tutorial see here: https://www.codecademy.com/article/how-to-use-jupyter-notebooks
You can also run a Jupyter notebook via VSCode. Here is the full guide: https://code.visualstudio.com/docs/datascience/jupyter-notebooks
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try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - sinhp/mcfds · GitHub
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LICENSE
LICENSE
Mapper.ipynb
Mapper.ipynb
Persistent_Homology.ipynb
Persistent_Homology.ipynb
Topological_data_analysis_final.pdf
Topological_data_analysis_final.pdf
eckart-young.ipynb
eckart-young.ipynb
environment.yml
environment.yml
hw1.ipynb
hw1.ipynb
hw2.ipynb
hw2.ipynb
hw2_soln.ipynb
hw2_soln.ipynb
hw3.ipynb
hw3.ipynb
hw4.ipynb
hw4.ipynb
make-up-corrected.pdf
make-up-corrected.pdf
make-up.pdf
make-up.pdf
markov-chain.png
markov-chain.png
matrix_basics.ipynb
matrix_basics.ipynb
notes_on_perpendicular_least_squares_and_svd.pdf
notes_on_perpendicular_least_squares_and_svd.pdf
pca.ipynb
pca.ipynb
plot_helper.py
plot_helper.py
readme.md
readme.md
requirements.txt
requirements.txt
svd-example.ipynb
svd-example.ipynb
Repository files navigation
If you have not done already you need to install Anaconda first.
Install the Dependencies
The notebooks are compatible with Python version 3.5 or later, all packages required are listed in environment.yml and requirements.txt. Pick any option below to install the dependencies:
Create a conda environment
Open your Terminal (or Command Prompt on Windows).
Use environment.yml to create a conda environment by executing the following command line:
conda env create -f environment.yml

This creates a conda environment named "mcfds_LinAlg". For conda 4.6 and later versions, activate this environment with
conda activate mcfds_LinAlg

For conda version prior to 4.6, run source activate mcfds_LinAlg on Linux and MacOS, activate mcfds_LinAlg on Windows.
Install with conda
conda install matplotlib numpy scipy jupyter imageio ipywidgets

Install with pip
Install the packages using requirements.txt for pip:
pip install -r requirements.txt

Check Installation
Run the script check_install.py to check whether the required packages are installed correctly:
python check_install.py

Opening and running Jupyter Notebooks
To launch a Jupyter notebook, open your terminal and navigate to the directory where you would like to save your notebook. Then type the command jupyter notebook in the your terminal (at the directory where you have saved your notebook) and the program will instantiate a local server at localhost:8888 (or another specified port). For more detailed tutorial see here: https://www.codecademy.com/article/how-to-use-jupyter-notebooks
You can also run a Jupyter notebook via VSCode. Here is the full guide: https://code.visualstudio.com/docs/datascience/jupyter-notebooks
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if (!enabled) return;
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filter: invert(1) hue-rotate(180deg) !important;
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pre code, pre code * {
filter: none !important;
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/* Fix common UI elements */
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filter: invert(1) hue-rotate(180deg) !important;
background: #2d2d44 !important;
border-color: #444 !important;
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/* Scrollbars */
::-webkit-scrollbar { background: #1a1a2e !important; }
::-webkit-scrollbar-thumb { background: #444 !important; }
::-webkit-scrollbar-thumb:hover { background: #555 !important; }
/* Selection */
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::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
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}
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var style = document.getElementById('universal-dark-mode-style');
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applyDarkMode();
console.log('[Universal Dark Mode] Enabled');
} else {
removeDarkMode();
console.log('[Universal Dark Mode] Disabled');
}
}
});
// Apply on load
applyDarkMode();
// Re-apply on dynamic content
var observer = new MutationObserver(function(mutations) {
if (enabled && !document.getElementById('universal-dark-mode-style')) {
applyDarkMode();
}
});
observer.observe(document.head, { childList: true });
console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');
})();
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();
GitHub - sinhp/mcfds · GitHub
Skip to content
BranchesTags
Latest commit
History
75 Commits
Folders and files
NameName
Last commit message
Last commit date
Projects
Projects
__pycache__
__pycache__
assets
assets
scripts
scripts
HW3_solutions.pdf
HW3_solutions.pdf
HW4_solutions.pdf
HW4_solutions.pdf
LICENSE
LICENSE
Mapper.ipynb
Mapper.ipynb
Persistent_Homology.ipynb
Persistent_Homology.ipynb
Topological_data_analysis_final.pdf
Topological_data_analysis_final.pdf
eckart-young.ipynb
eckart-young.ipynb
environment.yml
environment.yml
hw1.ipynb
hw1.ipynb
hw2.ipynb
hw2.ipynb
hw2_soln.ipynb
hw2_soln.ipynb
hw3.ipynb
hw3.ipynb
hw4.ipynb
hw4.ipynb
make-up-corrected.pdf
make-up-corrected.pdf
make-up.pdf
make-up.pdf
markov-chain.png
markov-chain.png
matrix_basics.ipynb
matrix_basics.ipynb
notes_on_perpendicular_least_squares_and_svd.pdf
notes_on_perpendicular_least_squares_and_svd.pdf
pca.ipynb
pca.ipynb
plot_helper.py
plot_helper.py
readme.md
readme.md
requirements.txt
requirements.txt
svd-example.ipynb
svd-example.ipynb
Repository files navigation
If you have not done already you need to install Anaconda first.
Install the Dependencies
The notebooks are compatible with Python version 3.5 or later, all packages required are listed in environment.yml and requirements.txt. Pick any option below to install the dependencies:
Create a conda environment
Open your Terminal (or Command Prompt on Windows).
Use environment.yml to create a conda environment by executing the following command line:
conda env create -f environment.yml

This creates a conda environment named "mcfds_LinAlg". For conda 4.6 and later versions, activate this environment with
conda activate mcfds_LinAlg

For conda version prior to 4.6, run source activate mcfds_LinAlg on Linux and MacOS, activate mcfds_LinAlg on Windows.
Install with conda
conda install matplotlib numpy scipy jupyter imageio ipywidgets

Install with pip
Install the packages using requirements.txt for pip:
pip install -r requirements.txt

Check Installation
Run the script check_install.py to check whether the required packages are installed correctly:
python check_install.py

Opening and running Jupyter Notebooks
To launch a Jupyter notebook, open your terminal and navigate to the directory where you would like to save your notebook. Then type the command jupyter notebook in the your terminal (at the directory where you have saved your notebook) and the program will instantiate a local server at localhost:8888 (or another specified port). For more detailed tutorial see here: https://www.codecademy.com/article/how-to-use-jupyter-notebooks
You can also run a Jupyter notebook via VSCode. Here is the full guide: https://code.visualstudio.com/docs/datascience/jupyter-notebooks
About
No description, website, or topics provided.
Resources
Readme
MIT license
Activity
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15 forks
Report repository
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