diff --git a/mkdocs.yml b/mkdocs.yml
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+site_name: Data Science Workflow Management
+site_description: 'Data Science Workflow Management'
+site_author: Ibon MartÃnez-Arranz
+site_url: https://github.com/imarranz/data-science-workflow-management
+repo_url: https://github.com/imarranz/data-science-workflow-management
+
+docs_dir: srcsite
+site_dir: website
+
+use_directory_urls: false
+
+theme:
+ name: readthedocs #mkdocs # https://mkdocs.readthedocs.io/en/0.13.3/user-guide/styling-your-docs/l
+ #custom_dir: mkdocs-bootstrap4-master/mkdocs_bootstrap4
+ color_mode: auto
+ #user_color_mode_toggle: true
+ palette:
+ primary: 'yellow'
+ accent: 'deep orange'
+ social:
+ - type: github-alt
+ link: https://github.com/imarranz
+ - type: twitter
+ link: https://twitter.com/imarranz
+ - type: linkedin
+ link: https://www.linkedin.com/in/ibon-martinez-arranz/
+ nav_style: dark #primary #dark
+ locale: en
+ highlightjs: true
+ hljs_languages:
+ - yaml
+ - python
+ - bash
+ include_sidebar: true
+ include_homepage_in_sidebar: true
+ prev_next_buttons_location: top #bottom # bottom, top, both, none.
+ titles_only: true
+ shortcuts:
+ help: 191 # ?
+ next: 78 # n
+ previous: 80 # p
+ search: 83 # s
+
+# conda install -c conda-forge pymdown-extensions
+# https://squidfunk.github.io/mkdocs-material/extensions/pymdown/
+
+markdown_extensions:
+ - toc:
+ permalink: "#"
+ baselevel: 1
+ toc_depth: 6
+ separator: "_"
+ - footnotes
+ - fenced_code
+
+plugins:
+ - search
+
+extra:
+ version: 1.0
+
+extra_css:
+ - 'css/custom.css'
+
+extra_javascript:
+# - 'javascripts/extra.js'
+ - 'https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-MML-AM_CHTML'
+
+nav:
+ - 'Data Science Workflow Management': index.md
+ - 'Introduction':
+ - 'Introduction': 01_introduction/011_introduction.md
+ - 'What is Data Science Workflow Management?': 01_introduction/012_introduction.md
+ - 'References': 01_introduction/013_introduction.md
+ - 'Fundamentals of Data Science':
+ - 'Fundamentals of Data Science': 02_fundamentals/021_fundamentals_of_data_science.md
+ - 'What is Data Science?': 02_fundamentals/022_fundamentals_of_data_science.md
+ - 'Data Science Process': 02_fundamentals/023_fundamentals_of_data_science.md
+ - 'Programming Languages for Data Science': 02_fundamentals/024_fundamentals_of_data_science.md
+ - 'Data Science Tools and Technologies': 02_fundamentals/025_fundamentals_of_data_science.md
+ - 'References': 02_fundamentals/026_fundamentals_of_data_science.md
+ - 'Workflow Management Concepts':
+ - 'Workflow Management Concepts': 03_workflow/031_workflow_management_concepts.md
+ - 'What is Workflow Management?': 03_workflow/032_workflow_management_concepts.md
+ - 'Why is Workflow Management Important?': 03_workflow/033_workflow_management_concepts.md
+ - 'Workflow Management Models': 03_workflow/034_workflow_management_concepts.md
+ - 'Workflow Management Tools and Technologies': 03_workflow/035_workflow_management_concepts.md
+ - 'Enhancing Collaboration and Reproducibility through Project Documentation': 03_workflow/036_workflow_management_concepts.md
+ - 'Practical Example': 03_workflow/037_workflow_management_concepts.md
+ - 'References': 03_workflow/038_workflow_management_concepts.md
+ - 'Project Planning':
+ - 'Project Planning': 04_project/041_project_plannig.md
+ - 'What is Project Planning?': 04_project/042_project_plannig.md
+ - 'Problem Definition and Objectives': 04_project/043_project_plannig.md
+ - 'Selection of Modelling Techniques': 04_project/044_project_plannig.md
+ - 'Selection Tools and Technologies': 04_project/045_project_plannig.md
+ - 'Workflow Design': 04_project/046_project_plannig.md
+ - 'Practical Example': 04_project/047_project_plannig.md
+ - 'Data Adquisition':
+ - 'Data Adquisition and Preparation': 05_adquisition/051_data_adquisition_and_preparation.md
+ - 'What is Data Adqusition?': 05_adquisition/052_data_adquisition_and_preparation.md
+ - 'Selection of Data Sources': 05_adquisition/053_data_adquisition_and_preparation.md
+ - 'Data Extraction and Transformation': 05_adquisition/054_data_adquisition_and_preparation.md
+ - 'Data Cleaning': 05_adquisition/055_data_adquisition_and_preparation.md
+ - 'Data Integration': 05_adquisition/056_data_adquisition_and_preparation.md
+ - 'Practical Example': 05_adquisition/057_data_adquisition_and_preparation.md
+ - 'References': 05_adquisition/058_data_adquisition_and_preparation.md
+ - 'Exploratory Data Analysis':
+ - 'Exploratory Data Analysis': 06_eda/061_exploratory_data_analysis.md
+ - 'Descriptive Statistics': 06_eda/062_exploratory_data_analysis.md
+ - 'Data Visualization': 06_eda/063_exploratory_data_analysis.md
+ - 'Correlation Analysis': 06_eda/064_exploratory_data_analysis.md
+ - 'Data Transformation': 06_eda/065_exploratory_data_analysis.md
+ - 'Practical Example': 06_eda/066_exploratory_data_analysis.md
+ - 'References': 06_eda/067_exploratory_data_analysis.md
+ - 'Modelling and Data Validation':
+ - 'Modelling and Data Validation': 07_modelling/071_modeling_and_data_validation.md
+ - 'What is Data Modelling': 07_modelling/072_modeling_and_data_validation.md
+ - 'Selection of Modelling Algortihms': 07_modelling/073_modeling_and_data_validation.md
+ - 'Model Training and Validation': 07_modelling/074_modeling_and_data_validation.md
+ - 'selection of Best Model': 07_modelling/075_modeling_and_data_validation.md
+ - 'Model Evaluation': 07_modelling/076_modeling_and_data_validation.md
+ - 'Model Interpretability': 07_modelling/077_modeling_and_data_validation.md
+ - 'Practical Example': 07_modelling/078_modeling_and_data_validation.md
+ - 'References': 07_modelling/079_modeling_and_data_validation.md
+ - 'Model Implementation':
+ - 'Model Implementation and Maintenance': 08_implementation/081_model_implementation_and_maintenance.md
+ - 'What is Model Implementation?': 08_implementation/082_model_implementation_and_maintenance.md
+ - 'selection of Implementation Platform': 08_implementation/083_model_implementation_and_maintenance.md
+ - 'Integration with Existing Systems': 08_implementation/084_model_implementation_and_maintenance.md
+ - 'Testing and Validation of the Model': 08_implementation/085_model_implementation_and_maintenance.md
+ - 'Model Maintenance and Updating': 08_implementation/086_model_implementation_and_maintenance.md
+ - 'Monitoring and Improvement':
+ - 'Monitoring and Improvement': 09_monitoring/091_monitoring_and_continuos_improvement.md
+ - 'What is Monitoring and Continuous Improvement?': 09_monitoring/092_monitoring_and_continuos_improvement.md
+ - 'Model Performance Monitoring': 09_monitoring/093_monitoring_and_continuos_improvement.md
+ - 'Problem Identification': 09_monitoring/094_monitoring_and_continuos_improvement.md
+ - 'Continuous Model Improvement': 09_monitoring/095_monitoring_and_continuos_improvement.md
+ - 'References': 09_monitoring/096_monitoring_and_continuos_improvement.md
+
+
+copyright: 'Data Science Workflow Management
Copyright © 2024 Ibon MartÃnez-Arranz
'
+
+
+#copyright: 'Essential Guide to Pandas
+#
+#
+#
+#
+#
Copyright © 2024
'