├── .gitignore ├── 01 - Software_Engineering ├── 01 - tm - software engineering practices - pt. I.html ├── 01 - tm - software engineering practices - pt. I.ipynb ├── 02 - tm - software engineering practices - pt. II .html ├── 02 - tm - software engineering practices - pt. II .ipynb ├── 03 - tm - object oriented programming - pt. I.html ├── 03 - tm - object oriented programming - pt. I.ipynb ├── 04 - tm - object oriented programming - pt. II.html ├── 04 - tm - object oriented programming - pt. II.ipynb ├── 05 - tm - Upload a Package to PyPi.html ├── 05 - tm - Upload a Package to PyPi.ipynb ├── OOP - 01 - syntax_shirt_practice │ ├── answer.py │ ├── shirt_exercise.ipynb │ └── tests.py ├── OOP - 02 - syntax_pants_practice │ ├── answer.py │ └── exercise.ipynb ├── OOP - 03 - code_gaussian_class │ ├── answer.py │ ├── gaussian_code_exercise.ipynb │ ├── numbers.txt │ └── test.py ├── OOP - 04 - code_magic_methods │ ├── answer.py │ ├── magic_methods.ipynb │ └── numbers.txt ├── OOP - 05 - code_inheritance_clothing │ ├── answer.py │ └── inheritance_exercise_clothing.ipynb ├── OOP - 06 - code_inheritance_probability_distributions │ ├── inheritance_probability_distribution.ipynb │ └── numbers.txt ├── binomial_package │ ├── Binomialdistribution_challenge.py │ ├── distributions │ │ ├── Binomialdistribution.py │ │ ├── Gaussiandistribution.py │ │ ├── Generaldistribution.py │ │ └── __init__.py │ ├── numbers.txt │ ├── numbers_binomial.txt │ ├── setup.py │ └── test.py ├── compute_launch.py ├── env_name │ ├── Scripts │ │ ├── Activate.ps1 │ │ ├── activate │ │ ├── activate.bat │ │ ├── api-ms-win-core-console-l1-1-0.dll │ │ ├── api-ms-win-core-datetime-l1-1-0.dll │ │ ├── api-ms-win-core-debug-l1-1-0.dll │ │ ├── api-ms-win-core-errorhandling-l1-1-0.dll │ │ ├── api-ms-win-core-file-l1-1-0.dll │ │ ├── api-ms-win-core-file-l1-2-0.dll │ │ ├── api-ms-win-core-file-l2-1-0.dll │ │ ├── api-ms-win-core-handle-l1-1-0.dll │ │ ├── api-ms-win-core-heap-l1-1-0.dll │ │ ├── api-ms-win-core-interlocked-l1-1-0.dll │ │ ├── api-ms-win-core-libraryloader-l1-1-0.dll │ │ ├── api-ms-win-core-localization-l1-2-0.dll │ │ ├── api-ms-win-core-memory-l1-1-0.dll │ │ ├── api-ms-win-core-namedpipe-l1-1-0.dll │ │ ├── api-ms-win-core-processenvironment-l1-1-0.dll │ │ ├── api-ms-win-core-processthreads-l1-1-0.dll │ │ ├── api-ms-win-core-processthreads-l1-1-1.dll │ │ ├── api-ms-win-core-profile-l1-1-0.dll │ │ ├── api-ms-win-core-rtlsupport-l1-1-0.dll │ │ ├── api-ms-win-core-string-l1-1-0.dll │ │ ├── api-ms-win-core-synch-l1-1-0.dll │ │ ├── api-ms-win-core-synch-l1-2-0.dll │ │ ├── api-ms-win-core-sysinfo-l1-1-0.dll │ │ ├── api-ms-win-core-timezone-l1-1-0.dll │ │ ├── api-ms-win-core-util-l1-1-0.dll │ │ ├── api-ms-win-crt-conio-l1-1-0.dll │ │ ├── api-ms-win-crt-convert-l1-1-0.dll │ │ ├── api-ms-win-crt-environment-l1-1-0.dll │ │ ├── api-ms-win-crt-filesystem-l1-1-0.dll │ │ ├── api-ms-win-crt-heap-l1-1-0.dll │ │ ├── api-ms-win-crt-locale-l1-1-0.dll │ │ ├── api-ms-win-crt-math-l1-1-0.dll │ │ ├── api-ms-win-crt-multibyte-l1-1-0.dll │ │ ├── api-ms-win-crt-private-l1-1-0.dll │ │ ├── api-ms-win-crt-process-l1-1-0.dll │ │ ├── api-ms-win-crt-runtime-l1-1-0.dll │ │ ├── api-ms-win-crt-stdio-l1-1-0.dll │ │ ├── api-ms-win-crt-string-l1-1-0.dll │ │ ├── api-ms-win-crt-time-l1-1-0.dll │ │ ├── api-ms-win-crt-utility-l1-1-0.dll │ │ ├── concrt140.dll │ │ ├── deactivate.bat │ │ ├── easy_install-3.6.exe │ │ ├── easy_install.exe │ │ ├── f2py.exe │ │ ├── msvcp140.dll │ │ ├── msvcp140_1.dll │ │ ├── msvcp140_2.dll │ │ ├── pip.exe │ │ ├── pip3.6.exe │ │ ├── pip3.exe │ │ ├── python.exe │ │ ├── python3.dll │ │ ├── python36.dll │ │ ├── pythonw.exe │ │ ├── tcl86t.dll │ │ ├── tk86t.dll │ │ ├── ucrtbase.dll │ │ ├── vccorlib140.dll │ │ ├── vcomp140.dll │ │ ├── vcruntime140.dll │ │ ├── xlwings32-0.11.8.dll │ │ └── xlwings64-0.11.8.dll │ └── pyvenv.cfg ├── python_package_example │ ├── distributions │ │ ├── Gaussiandistribution.py │ │ ├── Generaldistribution.py │ │ └── __init__.py │ └── setup.py ├── test_compute_launch.py └── test_sample.py ├── 02 - ML_in_Production ├── Deployment_Project │ ├── README.md │ ├── SageMaker Project.ipynb │ ├── Web App Diagram.svg │ ├── report.html │ ├── serve │ │ ├── model.py │ │ ├── predict.py │ │ ├── requirements.txt │ │ └── utils.py │ ├── train │ │ ├── model.py │ │ ├── requirements.txt │ │ └── train.py │ └── website │ │ └── index.html ├── Deployment_Project_compressed.zip ├── Introdution to Deployment.html ├── Introdution to Deployment.ipynb ├── Mini-Projects │ ├── 01 - IMDB Sentiment Analysis - XGBoost (Batch Transform) - Solution.html │ ├── 01 - IMDB Sentiment Analysis - XGBoost (Batch Transform) - Solution.ipynb │ ├── 02 - IMDB Sentiment Analysis - XGBoost (Hyperparameter Tuning) - Solution.html │ ├── 02 - IMDB Sentiment Analysis - XGBoost (Hyperparameter Tuning) - Solution.ipynb │ ├── 03 - IMDB Sentiment Analysis - XGBoost (Updating a Model) - Solution.ipynb │ ├── 03 - IMDB Sentiment Analysis - XGBoost (Updating a Model).html │ └── new_data.py ├── SageMaker - 01 - Building a Model.html ├── SageMaker - 01 - Building a Model.ipynb └── Tutorials │ ├── 01 - Boston Housing - XGBoost (Batch Transform) - High Level.html │ ├── 01 - Boston Housing - XGBoost (Batch Transform) - High Level.ipynb │ ├── 02 - Boston Housing - XGBoost (Batch Transform) - Low Level.html │ ├── 02 - Boston Housing - XGBoost (Batch Transform) - Low Level.ipynb │ ├── 03 - Boston Housing - XGBoost (Deploy) - High Level.html │ ├── 03 - Boston Housing - XGBoost (Deploy) - High Level.ipynb │ ├── 04 - Boston Housing - XGBoost (Deploy) - Low Level.html │ ├── 04 - Boston Housing - XGBoost (Deploy) - Low Level.ipynb │ ├── 05 - IMDB Sentiment Analysis - XGBoost - Web App.html │ ├── 05 - IMDB Sentiment Analysis - XGBoost - Web App.ipynb │ ├── 06 - Boston Housing - XGBoost (Hyperparameter Tuning) - High Level.html │ ├── 06 - Boston Housing - XGBoost (Hyperparameter Tuning) - High Level.ipynb │ ├── 07 - Boston Housing - XGBoost (Hyperparameter Tuning) - Low Level.html │ ├── 07 - Boston Housing - XGBoost (Hyperparameter Tuning) - Low Level.ipynb │ ├── 08 - Boston Housing - Updating an Endpoint.html │ ├── 08 - Boston Housing - Updating an Endpoint.ipynb │ ├── Web App Diagram.svg │ └── index.html ├── 03 - ML_SageMaker_Studies ├── 01 - Pop_Segmentation - PCA.html ├── 01 - Pop_Segmentation - PCA.ipynb ├── 02 - Fraud_Detection - LinearLearner.html ├── 02 - Fraud_Detection - LinearLearner.ipynb ├── 03 - Moon_Data │ ├── Moon_Classification - PyTorch.html │ ├── Moon_Classification.ipynb │ ├── data_moon │ │ └── train.csv │ └── source │ │ ├── model.py │ │ ├── predict.py │ │ └── train.py ├── 04 - Project_Plagiarism_Detection │ ├── 01 - Data_Exploration.ipynb │ ├── 02 - Plagiarism_Feature_Engineering.ipynb │ ├── 03 - Training_a_Model.ipynb │ ├── Containment_Solution.html │ └── Project_submission_Plagiarism_Detection │ │ ├── 1_Data_Exploration.ipynb │ │ ├── 2_Plagiarism_Feature_Engineering.ipynb │ │ ├── 3_Training_a_Model.ipynb │ │ ├── helpers.py │ │ ├── problem_unittests.py │ │ └── source_sklearn │ │ └── train2.py ├── 05 - Energy_Consumption_Exercise - DeepAR.html ├── 05 - Energy_Consumption_Solution - DeepAR.ipynb ├── 05b - Energy_Consumption_Solution - DeepAR.html ├── 06 - DeepAR_Synthetic.ipynb ├── 06 - DeepAR_synthetic.html ├── 07 - DeepAR_Electricity.html └── 07 - DeepAR_Electricity.ipynb ├── 04 - Capstone_Project ├── Capstone Proposal.ipynb ├── Capstone-project-TM │ ├── README.md │ ├── RNN_for_Time_Series_Forecasting.pdf │ ├── project_notebook.html │ ├── project_notebook.ipynb │ └── proposal.pdf ├── README.md ├── Tex │ ├── MLND_Capstone.aux │ ├── MLND_Capstone.dvi │ ├── MLND_Capstone.lof │ ├── MLND_Capstone.lot │ ├── MLND_Capstone.out │ ├── MLND_Capstone.out.ps │ ├── MLND_Capstone.pdf │ ├── MLND_Capstone.synctex.gz │ ├── MLND_Capstone.tex │ ├── MLND_Capstone.tex.bak │ ├── MLND_Capstone.toc │ ├── notebook.aux │ ├── notebook.out │ ├── notebook.pdf │ ├── notebook.synctex.gz │ └── notebook.tex ├── capstone-notes.md └── images │ ├── M4_daily_results.png │ ├── M4_data_forecast_horizon.png │ ├── M4_data_overview.png │ ├── M4_hourly_results.png │ ├── M4_monthly_results.png │ ├── M4_weekly_results.png │ └── train_test_plot_m4_hourly338.png ├── NLP_Fundamentals ├── Character-Level LSTM in PyTorch withGPU.html ├── Character-Level LSTM in PyTorch.html ├── Character-Level LSTM in PyTorch.ipynb ├── Implementation of RNN & LSTM.html ├── Implementation of RNN & LSTM.ipynb ├── Introduction to NLP.html ├── Introduction to NLP.ipynb ├── rnn_1_epoch.net └── rnn_20_epoch.net ├── README.md ├── data ├── all_coding_books.txt ├── anna.txt ├── books_published_last_two_years.txt ├── gift_costs.txt ├── numbers.txt └── winequality-red.csv └── images ├── MLND Certificate.png ├── charRNN.png ├── charseq.jpeg ├── cloud_iaas.png ├── cloud_paas.png ├── cloud_saas.png ├── container.png ├── container2.png ├── curve3.png ├── deploymentmodels.png ├── endpoint.png ├── endpoint2.png ├── endpoint3.png ├── essentialcharacteristics.png ├── httpmethods.png ├── mlworkflow.png ├── my_webapp.png ├── nistcloud.png ├── scatter1.png ├── sentiment_API.png ├── sequence_batching@1x.png └── sequence_batching_ex.png /.gitignore: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tm1611/Machine-Learning-Engineer-Nanodegree/HEAD/.gitignore -------------------------------------------------------------------------------- /01 - 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