Exercises
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Tutorial exercise contextWithImage |
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2.3. Tm package - Text preprocessing B |
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2.3. Markov Chain - Predicting with new probabilities |
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4. Wordclouds |
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Diagonal matrix |
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3.5. Clickstream - Modelling |
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3.1. Tidytext package - Text preprocessing |
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Function is_even() |
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7. Graph representation learning |
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Variables in a dataframe |
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1.3. Word embeddings - Plotting with t-SNE |
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Open Food Facts |
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Commute data |
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6.1. Homophily - Data and Network creation |
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Installed packages |
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Environments |
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Smartphone straling |
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Generating and displaying random pets |
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Product of cohort |
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Beaver data frames |
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Linear regression: gonorrhoea |
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Negative binomial distribution |
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2.2. Markov Chain - Predicting new patterns |
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Function args_and_body |
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1.1. PageRank - Dataframe Creation |
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3. QAP regression for one independent variable |
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2.1. Network representation via statnet - Starting from the adjacency matrix |
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1.3. Event Attendance - Partial dependency plots |
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Duitse tanks |
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2.3. Topic Modeling - Topics and documents |
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