Part 1: Introduction to Data Science for Humanities |
Notebook: Python-Basics (HTML-Version) |
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Kick-off slides |
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Part 2: (Re-)introduction to Python |
Notebook: Basics 2 (HTML-Version) |
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Part 3: Data modeling for data science |
Notebook: Numpy (HTML-Version) |
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Solution: Bag-of-words |
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Solution: Python basics |
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Part 4: Data Acquisition and Preparation |
Notebook: Acquistion and Preprocessing (HTML-Version) |
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Dataset: Olympics |
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Part 5: Explorative Analysis 1 – Descriptive Analysis and visualization |
Notebook: Descriptive Statistics (HTML-Version) |
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Notebook: Deep-dive into Seaborn (HTML-Version) |
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Part 6: Explorative Analysis 2 – Clustering and distance functions |
Notebook: Clustering and Distance Functions (HTML) |
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Notebook: Clustering and distance function (.ipynb) |
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Part 7: Predictive Analysis (A Gentle Introduction to Machine Learning) |
Notebook: Classification (.ipynb) |
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Data: reviews_train.csv |
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Data: reviews_text.csv |
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Text Classification and Clustering: Slides |
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Part 8: Text and Language I (Computational Linguistics) |
Notebook: Text Processing |
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Slides: Lexical Semantics |
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Slides: Text Representations |
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Slides: Information Extraction |
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Data: Unlabeled Reviews |
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