Credit: Anna Logue
Lecture Videos
The Data and Web Science Group records core lectures for Master students on video and provides screen casts of accompanying exercises in order to enable students to be more flexible in their learning patterns.
Up till now, we have recorded the Data Mining I, Data Mining II, Web Mining, Web Data Integration, Information Retrieval and Web Search, Text Analytics, Large-scale Data Management, Decision Support and Knowledge Mangement lectures and provide screen casts for the Data Mining I and Web Data Integration exercises.
Lots of thanks to the Referat Neue Medien of the Stabsstelle Studium und Lehre for supporting us in recording the lecture videos.
Please note that the videos can only be accessed from within the University of Mannheim. If students want to watch them from home, they need to connect to the university via VPN.
Lecture: Data Mining I
Instructor: Prof. Christian Bizer
Recorded: FSS2020Video: Introduction to Data Mining
Video: Cluster Analysis
Video: Classification – Part 1
Video: Classification – Part 2
Video: Classification – Part 3
Video: Regression
Video: Association Analysis
Video: Text Mining
Instructor: Prof. Heiko Paulheim
Recorded: HWS2020Video: Introduction to Data Mining
Video: Cluster Analysis
Video: Classification – Part 1
Video: Classification – Part 2
Video: Regression
Video: Text Mining
Video: Association Analysis
Tutorials & Exercises: Data Mining I
Python
Instructor: Ralph Peeters
Recorded: FSS2022The exercise sheets and the data sets for the exercise are available on the course page.
Screen cast: Simple Preprocessing and Visualization (Intro | Solution)
Screen cast: Association Analysis (Intro | Solution)
RapidMiner
Instructor: Robert Meusel
Recorded: FSS2015The exercise sheets and the data sets for the exercise are available on the course page.
Screen cast: Introduction to RapidMiner
Screen cast: Data Preprocessing
Screen cast: Exercise 1 – Exploring the Students Dataset
Screen cast: Exercise 2 – Customer Segmentation
Screen cast: Classification With RapidMiner
Screen cast: Optimization With RapidMiner
Screen cast: Exercise 3 – Credit Assignment
Screen cast: Exercise 4 – Shopping Basket Analysis
Screen cast: Text Mining With RapidMiner
Screen cast: Exercise 5 – News Article Clustering
Lecture: Data Mining II
Instructor: Prof. Heiko Paulheim
Recorded: FSS2015Video: Data Preprocessing
Video: Regression
Video: Anomaly Detection
Video: Ensembles
Video: Time Series Analysis
Video: Online Learning (by Robert Meusel)
Lecture: Machine Learning
Instructor: Prof. Dr. Rainer Gemulla
Recorded: HWS2020 (slides from HWS2022)1. Introduction
1. What is Machine Learning?
2. Types of Machine Learning
3. Basic Concepts & Summary2. Inference and Decision
1. Probability Refresher
2. Generative & Discriminative Models
3. Parameter Estimation
4. Decision & Summary3. Generative Models for Discrete Data
1. The Beta-Binomial Model
2. The Dirichlet-Multinomial Model
3. Naive Bayes & Summary4. Logistic Regression
1. Logistic Regression
2. Maximum Likelihood Estimation & Empirical Risk Minimization
3. Model Fitting
4. MAP Estimation
5. Softmax Regression & Summary5. Dimensionality Reduction
1. Matrix Decompositions
2. The Singular Value Decomposition
3. Interpreting the SVD
4. Using the SVD
5. Latent Linear Models & Wrap-Up6. The EM Algorithm & Mixture Models
1. Introduction
2. The EM Algorithm
3. Mixture Models & Summary7. Kernels and Vector Machines
1. Kernels
2. Kernel Machines & Vector Machines
3. The Kernel Trick
4. Support Vector Machines & Summary8. Hyperparameter Optimization
1. The Hyperparameter Optimization Problem
2. Blackbox Optimization
3. Multi-Fidelity Optimization
4. HPO in PracticeA. Probability Refresher
B. Vectors and Matrices
1. Vectors
2. Matrices & SummaryLecture: Large-Scale Data Management
Lecture: Web Data Integration
Instructor: Prof. Christian Bizer
Recorded: HWS2019Video: Identity Resolution – Part I
Tutorials: Web Data Integration
Instructor: Anna Primpeli
Recorded: HWS2019MapForce can be downloaded from the Altova website including a 30-day test licence. The Java Framework which is used for Identity Resolution and Data Fusion can be downloaded here.
Tutorial and screen cast: Introduction to MapForce
Tutorial and screen cast: Introduction to Java Identity Resolution Framework
Screen cast: Introduction to Java Data Fusion Framework
Lecture: Text Analytics
Instructor: Prof. Simone Ponzetto
Recorded: HWS2015Video: Linguistics Essentials and Statistics Fundamentals for NLP
Video: Words and Transducers
Video: Collocations
Video: POS Tagging Part I
Video: POS Tagging Part II
Video: Word Sense Disambiguation
Video: Information Extraction
Video: Machine Translation
Video: Vector Semantics (Sparse)
Video: Deep learning for NLP
Lecture: Web Mining
Instructor:Prof. Dr. Christian Bizer & Prof. Dr. Simone Ponzetto
Recorded: FSS2022Web Search and Information Retrieval
Instructor: Dr. Laura Dietz
Recorded: FSS2016Video: Boolean Retrieval
Video: Evaluation
Video: Query Expansion
Video: Probabilistic IR, BIM, BM25
Video: Language Models for IR
Video: Web Crawling
Video: Link Analysis
Video: Learning to Rank
Lecture: Semantic Web Technologies
Instructor:Prof. Dr. Heiko Paulheim
Recorded: HWS2016Video: Introduction
Video: RDF
Video: RDFS
Video: SPARQL
Video: OWL Part I
Video: OWL Part II
Video: Ontology Engineering
Lecture: Knowledge Management
Instructor: Prof. Dr. Simone Paolo Ponzetto
Recorded: FSS2017Video: Data Mining II (Clustering)
Video: Data Mining III (Evaluation)
Lecture: Decision Support