River Hydraulics and Modeling: Semi-Distributed Approach

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (32)

Model Selection Criteria: AIC, BIC, Cp

Explores model selection criteria like AIC, BIC, and Cp in statistics for data science.

Air Pollution Data Analysis

Covers the analysis of air pollution data, focusing on R basics, visualizing time series, and creating summaries of pollutant concentrations.

Gaussian Mixture Models: Data Classification

Explores denoising signals with Gaussian mixture models and EM algorithm, EMG signal analysis, and image segmentation using Markovian models.

Decision Trees: Classification

Explores decision trees for classification, entropy, information gain, one-hot encoding, hyperparameter optimization, and random forests.

Python Modules and Functions

Covers Python libraries, modules, scoping, functions, lambdas, and practical examples.

Comsol: Parallel plate capacitor

Focuses on modeling a parallel plate capacitor using Comsol, emphasizing clear project ideas and group collaboration.

Homology of Riemann Surfaces

Explores the homology of Riemann surfaces, including singular homology and the standard n-simplex.

Theory Discussion: Degrees of Freedom Analysis and Solving Methods

Discusses degrees of freedom analysis and solving methods in energy conversion flowsheets.

Deep Learning Building Blocks

Covers tensors, loss functions, autograd, and convolutional layers in deep learning.

Big Data Best Practices and Guidelines

Covers best practices and guidelines for big data, including data lakes, architecture, challenges, and technologies like Hadoop and Hive.

Advanced Pandas Functions

Focuses on advanced pandas functions for data manipulation, exploration, and visualization with Python, emphasizing the importance of understanding and preparing data.

In Silico Neuroscience: Data Reproducibility and Reusability

Emphasizes data reproducibility and reusability in in silico neuroscience, focusing on neuroinformatics tools and methods.

Page 2 of 2