Data Science Code Repository

Data Science and Machine Learning Code Repository that I made in my Master in Data Science

Table of Contents and Code Notebooks

**Helpful Resources for Novels Data Scientist **

To access the code materials for a given chapter, simply click on the open dir links next to the chapter headlines to navigate to the chapter subdirectories located in the code/ subdirectory. You can also click on the ipynb or R Code links below to open and view the Jupyter notebook, R Code, or Python Code of each chapter directly on GitHub.

By Armando Olivares.

1. Machine Learning - PCA and Clusteinr [open dir] [RMD]
2. Training Machine Learning Algorithms for Graphs Analyis [open dir] [RMD]
3. A Tour of Machine Learning for Clustering [open dir] [ipynb]
4. Building Good Training Sets – Data Pre-Processing [open dir] [ipynb]
5. Compressing Data via Dimensionality Reduction [open dir] [ipynb]
6. Learning Best Practices for Model Evaluation and Hyperparameter Optimization [open dir] [ipynb]
7. Combining Different Models for Ensemble Learning for Fraud Detection [open dir] [ipynb]
8. Applying RNN to Sentiment Analysis [[open dir](./Sentiment_analysis] [ipynb]
9. Embedding a Machine Learning Model into a Web Application using Spotify API to Get the Data [open dir] [py]
10. Predicting Housing Values with a Tour for Regression Analysis [open dir] [ipynb]
11. Working with Geolocation Data for Marketing [open dir] [Rcode]
12. Time Series Analysis [open dir] [RCode]
13. Churn Prediction Case of Study [open dir] [R Code]
14. Implementing Deep Convolutional Neural Networks with Keras [open dir] [ipynb]
15. Recommender System [open dir] [ipynb]
16. Machine Learning with Spark [open dir] [Python Code]
17. End to end Regression for a continous outcome [open dir] [Python Code]

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