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relataly-public-python-tutorials

Welcome to the GitHub tutorial directory of the relataly.com blog on python machine learning!

The files listed in this directory are all Jupyter notebook files.

Each file represents a separate Python project and is described in more detail in a blog post.

For access to blog articles visit www.relataly.com.

Also check out the other relataly repositories: https://github.com/flo7up/relataly-public-python-API-tutorials

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Name		Name	Last commit message	Last commit date
Latest commit History 150 Commits
.ipynb_checkpoints		.ipynb_checkpoints
data		data
.gitignore		.gitignore
001 Time Series Forecasting - Forecasting US Beer Sales with (auto) ARIMA.ipynb		001 Time Series Forecasting - Forecasting US Beer Sales with (auto) ARIMA.ipynb
003 Time Series Forecasting - Univariate Model using Recurrent Neural Networks.ipynb		003 Time Series Forecasting - Univariate Model using Recurrent Neural Networks.ipynb
004 Time Series Forecasting - Adjusting Prediction Intervals.ipynb		004 Time Series Forecasting - Adjusting Prediction Intervals.ipynb
005 Time Series Forecasting - Multi-step Rolling Forecasting.ipynb		005 Time Series Forecasting - Multi-step Rolling Forecasting.ipynb
006 Time Series Forecasting - Multi-Output Regression.ipynb		006 Time Series Forecasting - Multi-Output Regression.ipynb
007 Time Series Forecasting - Multivariate Time Series Models.ipynb		007 Time Series Forecasting - Multivariate Time Series Models.ipynb
008 Time Series Forecasting - Feature Engineering for Multivariate Models.ipynb		008 Time Series Forecasting - Feature Engineering for Multivariate Models.ipynb
009 Time Series Forecasting - Measuring Model Performance.ipynb		009 Time Series Forecasting - Measuring Model Performance.ipynb
013 Simple Sentiment Analysis using Bayes and Logistic Regression.ipynb		013 Simple Sentiment Analysis using Bayes and Logistic Regression.ipynb
016 Grid Search for Hyperparameter Tuning of RandomDecisionForests.ipynb		016 Grid Search for Hyperparameter Tuning of RandomDecisionForests.ipynb
017 Customer Churn Prediction using Random Decision Forest and Permutation Feature Importance.ipynb		017 Customer Churn Prediction using Random Decision Forest and Permutation Feature Importance.ipynb
018 Classifying Cats & Dogs Binary.ipynb		018 Classifying Cats & Dogs Binary.ipynb
019 Classifying Shopper Buying Intention using Logistic Regression.ipynb		019 Classifying Shopper Buying Intention using Logistic Regression.ipynb
020 Color-Coded Cryptocurrency Price Charts.ipynb		020 Color-Coded Cryptocurrency Price Charts.ipynb
023 Forecasting Criminal Activity in San Francisco.ipynb		023 Forecasting Criminal Activity in San Francisco.ipynb
025 Building a Twitter Bot with Python.ipynb		025 Building a Twitter Bot with Python.ipynb
026 Multivariate Anomaly Detection - Using Isolation Forests to fight Credit Card Fraud with Python.ipynb		026 Multivariate Anomaly Detection - Using Isolation Forests to fight Credit Card Fraud with Python.ipynb
031 Building a Movie Recommender using Collaborative Filtering with Python.ipynb		031 Building a Movie Recommender using Collaborative Filtering with Python.ipynb
041 Clustering using K-means with Python.ipynb		041 Clustering using K-means with Python.ipynb
070 Visualizing Geographic Data using Python.ipynb		070 Visualizing Geographic Data using Python.ipynb
112 Correlation Matrix - COVID-19 and Financial Assets.ipynb		112 Correlation Matrix - COVID-19 and Financial Assets.ipynb
README.md		README.md

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