The listed learning units belong to the course Big Data Analytics. Do you want to access all course content?
2.1 Basics in Statistics
Video
2.1 Basics in Statistics
Learning materials
2.2 Probability Theory
Video
2.2 Probability Theory
Learning materials
2.3 Clustering
Video
2.3 Clustering
Learning materials
2.4 k-Means Clustering
Video
2.4 k-Means Clustering
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2.5 Clustering Evaluation
Video
2.5 Clustering Evaluation
Learning materials
Hausaufgabe Woche 2
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Lesematerial
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3.1 Density-based Clustering
Video
3.1 Density-based Clustering
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3.2 Hierarchical Clustering
Video
3.2 Hierarchical Clustering
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3.3 Density-based hierarchical clustering
Video
3.3 Density-based hierarchical clustering
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3.4 Classification
Video
3.4 Classification
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3.5 Decision trees
Video
3.5 Decision trees
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3.6 Decision tree pruning
Video
Hausaufgabe Woche 3
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Lesematerial
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4.1 Nearest Neighbour Classification
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4.1 Nearest Neighbour Classification
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4.2 Bayesian Classifier - Teil 1
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4.3 Bayesian Classifier - Teil 2
Video
4.3 Bayesian Classifier
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4.4 Linear Classifier
Video
4.5 Support Vector Machines
Video
4.5 Support Vector Machines
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4.6 Ensemble Classification
Video
4.6 Ensemble Classification
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Lesematerial
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Hausaufgabe Woche 4
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5.1 Frequent Itemset Mining
Video
5.1 Frequent Itemset Mining
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5.2 Apriori Algorithm
Video
5.2 Apriori Algorithm
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5.3 Frequent Pattern Tree
Video
5.3 Frequent Pattern Tree
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5.4 Frequent Pattern Growth
Video
5.4 Frequent Pattern Growth
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5.5 Maximal Frequent Itemsets
Video
5.5 Maximal Frequent Itemsets
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5.6 Association Rules
Video
5.6 Association Rules
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Hausaufgabe Woche 5
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Bonusaufgabe
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Lesematerial
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6.1 Outlier Mining
Video
Outlier Mining
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6.2 Distance-based Outlier Mining
Video
Distance-Based Outlier Mining
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6.3 Density-based Outlier Mining
Video
Density-Based Outlier Mining
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6.4 Subspace Mining
Video
Subspace Mining
Learning materials
6.5 Stream Mining
Video
6.6 Graph Mining
Video
Stream & Graph Mining
Learning materials
6.7 M. Sc. Data Engineering
Video
Hausaufgabe Woche 6
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Lesematerial
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