Renku: Collaborative Data Science

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Related lectures (32)

Page 1 of 4

Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.

Data Science Visualization with Pandas

Covers data manipulation and exploration using Python with a focus on visualization techniques.

Critical Data Studies: Reproducibility and Renku

Explores the significance of reproducibility in data science and introduces Renku, a platform for managing data-driven projects.

General Introduction to Data Science

Offers a comprehensive introduction to Data Science, covering Python, Numpy, Pandas, Matplotlib, and Scikit-learn, with a focus on practical exercises and collaborative work.

Quantum Chemistry

Covers eigenvalues, eigenfunctions, Hermitian operators, and the measurement of observables in quantum chemistry.

Decision Tree Classification

Covers decision tree classification using KNIME Analytics Platform for data preprocessing and model creation.

General Introduction to Big Data

Covers data science tools, Hadoop, Spark, data lake ecosystems, CAP theorem, batch vs. stream processing, HDFS, Hive, Parquet, ORC, and MapReduce architecture.

Image Processing in Fiji

Covers the basics of image processing using Fiji software, focusing on managing files and applying filters.

Total scattering and PDF analysis

Explores total scattering and PDF analysis in materials science, covering in-situ synthesis, data analysis techniques, and applications in host-guest systems.

Matrix to Density Operator

Explains the transformation from a matrix to the density operator in quantum physics.