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https://github.com/Labaile/functional_intro_to_python#python-programming-recipes
Immutability example notebookhttps://colab.research.google.com/drive/1hZsv6KyzIHD4viFBvCYFrGaQb6Tqu4Sw
https://github.com/Labaile/functional_intro_to_python#managed-ml-and-iot
Managed Machine Learning Systems and Internet of Thingshttps://github.com/noahgift/managed_ml_systems_and_iot
https://github.com/Labaile/functional_intro_to_python#software-carpentary--testing-linting-building
How Create a Python Project Github Repositoryhttps://github.com/noahgift/myrepo
How to Write "Clean" Code in Python (2010) Using Pylinthttps://www.ibm.com/developerworks/aix/library/au-cleancode/
How to Test Jupyter Notebooks with Pytesthttps://github.com/noahgift/functional_intro_to_python/blob/master/Makefile#L9
How to build and test a Python Project with CircleCIhttps://github.com/noahgift/functional_intro_to_python/blob/master/.circleci/config.yml
How to get test Coverage with Pytesthttps://github.com/noahgift/devml/blob/master/Makefile#L8
How to use Pylint to Fail on Error and Warnings onlyhttps://github.com/noahgift/devml/blob/master/Makefile#L22
Increase reliability in data science and machine learning projects with CircleCIhttps://circleci.com/blog/increase-reliability-in-data-science-and-machine-learning-projects-with-circleci/
https://github.com/Labaile/functional_intro_to_python#concurrency-in-python
IBM Developerworks: Writing Multi-Threaded Programs in Python (2008)https://www.ibm.com/developerworks/aix/library/au-threadingpython/
IBM Developerworks: Using Multi-processing Module in Python (2009)https://www.ibm.com/developerworks/aix/library/au-multiprocessing/index.html
Writing Async Network IO Calls to AWS APIhttps://github.com/noahgift/awsasync
Worker Farm with RabbitMQ and Tornadohttps://github.com/noahgift/tornado_rabbitmq_linear_optimization
Nuclear Powered Command-Line Tools: GPU/CUDA, JIT, Multi-threaded JIThttps://github.com/noahgift/nuclear_powered_command_line_tools
https://github.com/Labaile/functional_intro_to_python#cloud-computing-aws-sentiment-analysis
AWS Sentiment Analysis Notebookhttps://github.com/noahgift/recommendations/blob/master/notebooks/NLP_AWS.ipynb
https://github.com/Labaile/functional_intro_to_python#recommendation-engines
Hand coded tanimoto and Pandas similarity enginehttps://github.com/noahgift/recommendations/tree/master/tanimoto_example
https://github.com/Labaile/functional_intro_to_python#cloud-computing-azure-sentiment-analysis
NLP on Azurehttps://github.com/noahgift/recommendations/blob/master/notebooks/Azure_Sentiment_Analysis.ipynb
https://github.com/Labaile/functional_intro_to_python#cloud-computing-aws
AWS + Boto: Python and AWS Jupyter Notebookhttps://github.com/noahgift/functional_intro_to_python/blob/master/notebooks/aws/aws.ipynb
AWS + Boto: Launching Spot Instances From Pythonhttps://github.com/noahgift/spot_price_machine_learning/blob/master/spot_launcher.py
AWS + Boto: Calling Spot Instance API to Create CLI Machine Learning Toolhttps://github.com/noahgift/spot_price_machine_learning/blob/master/spot-price-ml.py
AWS + Boto: Spot Price Jupyter Notebook Explorationhttps://github.com/noahgift/spot_price_machine_learning/blob/master/notebooks/spot_pricing_ml.ipynb
https://github.com/Labaile/functional_intro_to_python#cloud-computing-gcp
Google Sheets to Pandas DataFramehttps://github.com/noahgift/pragmaticai-gcp/blob/master/notebooks/dataflow_sheets_to_pandas.ipynb
BigQuery to Pandas to Seabornhttps://github.com/noahgift/pragmaticai-gcp/blob/master/notebooks/pragai-big-instance-BigQuery.ipynb
NLP on Google Cloudhttps://github.com/noahgift/recommendations/blob/master/notebooks/NLP_GCP.ipynb
https://github.com/Labaile/functional_intro_to_python#machine-learning-and-data-science-full-jupyter-notebooks
DEVML: Datascience around Githubhttps://github.com/noahgift/devml
Social Power NBA: Datascience around the NBA and Social Mediahttps://github.com/noahgift/socialpowernba
Spot Price ML(KMeans Unsupervized Machine Learning Recommender): Datascience around AWS Spot Priceshttps://github.com/noahgift/spot_price_machine_learning
https://github.com/Labaile/functional_intro_to_python#data-visualization
https://github.com/Labaile/functional_intro_to_python#seaborn-examples
Visualizing Spot Prices in Seabornhttps://github.com/noahgift/spot_price_machine_learning/blob/master/notebooks/spot_pricing_ml.ipynb
Correlation Heatmap in Seaborn for NBAhttps://github.com/noahgift/socialpowernba/blob/master/notebooks/exploring_team_valuation_nba.ipynb
https://github.com/Labaile/functional_intro_to_python#plotly
Exploring 30 years of Real Estate Prices with Zillow Data and Plotlyhttps://github.com/noahgift/real_estate_ml/blob/master/notebooks/explore_zillow_data_sets.ipynb
https://github.com/Labaile/functional_intro_to_python#creating-commandline-tools
Python Commandline tool Rosetta: Comparing R, Bash, Go, Node, Python and Rubyhttps://github.com/noahgift/cli-rosetta
Pyli: Deduplication Commandline Tool That Walks A Filesystemhttps://github.com/nogibjj/pyli
Developersworks Article (2008): Creating Commandline Tools Pythonhttps://www.ibm.com/developerworks/aix/library/au-pythocli/
Nuclear Powered Commandline toolshttps://github.com/noahgift/nuclear_powered_command_line_tools
https://github.com/Labaile/functional_intro_to_python#creating-a-complete-data-engineering-api
Real world Data Engineering APIhttps://github.com/noahgift/pai-aws
https://github.com/Labaile/functional_intro_to_python#statically-generated-websites
Interfacing with Hugo and Algolia from Pythonhttps://github.com/noahgift/hugotools
https://github.com/Labaile/functional_intro_to_python#deploying-python-packages-to-pypi
Article on how to deploy commandline tools and libraries to PyPihttps://www.ibm.com/developerworks/opensource/library/ba-github-analytics-2/index.html
https://github.com/Labaile/functional_intro_to_python#web-scraping-in-python
Programatically Scraping Wikipedia API in Python: Pageviews and Articleshttps://github.com/noahgift/socialpowernba/blob/master/socialpower/spwikipedia.py
Using Python Twitter APIhttps://github.com/noahgift/socialpowernba/blob/master/socialpower/spwikipedia.py
Serverless Web Scraping with Lambda and Step Functionshttps://github.com/noahgift/web_scraping_python
https://github.com/Labaile/functional_intro_to_python#logging-in-python
"Sensible" Logging Library in Python: Deployed to PyPIhttps://github.com/nogibjj/sensible
https://github.com/Labaile/functional_intro_to_python#conceptual-machine-learning
https://github.com/Labaile/functional_intro_to_python#linear-regression
Linear Regression in Jupyter Notebookhttps://github.com/noahgift/socialpowernba/blob/master/notebooks/exploring_endorsement_revenue_nba.ipynb
https://github.com/Labaile/functional_intro_to_python#machine-learning-model-building-for-regression
ML Linear Regression with Yellowbrick and SKlearnhttps://github.com/noahgift/regression-concepts/blob/master/ml_regression.ipynb
https://github.com/Labaile/functional_intro_to_python#mathematical-and-algorithmic-programming
https://github.com/Labaile/functional_intro_to_python#optimization
IBM Developerworks Series on Pyomo (Linear Optimization in Python)https://www.ibm.com/developerworks/cloud/library/cl-optimizepythoncloud1/
Traveling Salesman (NP Hard Simulation Solution with Random, Greedy Start)https://github.com/noahgift/or/blob/master/tsp_greedy_random_start.py
Greedy Coin Example in Pythonhttps://github.com/noahgift/greedy_coin
https://github.com/Labaile/functional_intro_to_python#text
CC-BY-NC-ND licensehttps://github.com/noahgift/functional_intro_to_python/blob/master/license.md
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