Lectures related to Text Mining and Data Curation

In Silico Neuroscience: Data Reproducibility and Reusability

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

Graph Mining: Social Networks and Data Analysis

Explores graph mining in social networks, covering data analysis and community detection.

Text Mining: Long-tail Data and Brain Connectivity

Explores text mining of long-tail data in neuroscience and brain connectivity, including named entity recognition, protein concentration mining, and comparison of connectivity matrices.

Understanding Big Data in Neuroscience MOOC: Neuroscience Reconstructed: Genetics and Brain Development

Delves into Big Data in neuroscience, analyzing large datasets and addressing challenges in data organization, standardization, integration, and visualization.

Big Data: Processing and Dimensions

Explores Big Data generation, storage, processing, and dimensions, along with challenges in data analytics, cloud computing elasticity, and security.

Cosmological Puzzles: Dark Matter and Energy

Explores fundamental cosmological puzzles related to dark matter and energy.

Machine learning: Physics and Data

Delves into the intersection of physics and data in machine learning models, covering topics like atomic cluster expansion force fields and unsupervised learning.

Introduction to Data: Data Types and Quality

Covers data types, quantity, quality, and representativeness in the world of data.

Data Analysis to AI and ML, Social Media

Explores the evolution from data analysis to AI and ML, emphasizing big data, machine learning, and social media interaction.

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.

Neuroinformatics, Text Mining MOOC: Simulation Neurocience

Explores text mining in neuroinformatics to extract brain connectivity data and annotate model parameters from scientific literature.

Approaches and Rationale of Simulation Neuroscience MOOC: Simulation Neurocience

Explores the overview, rationale, and strategies of simulation neuroscience, emphasizing the challenges of reconstructing and simulating the brain.

Data Science in Personalized and Global Health: Privacy-Enhancing Technologies

Delves into data science in personalized and global health, emphasizing privacy-enhancing technologies and AI applications in healthcare.

Data Issues in Research

Explores challenges in data assumptions, biases, and more in research, including incomplete write-ups and frustrations of newcomers.

Data Preparedness: Improving Response through Information Management MOOC: A Resilient Future: Science and Technology for Disaster Risk Reduction

Emphasizes the importance of data preparedness in disaster response and explores strategies for addressing information gaps and overloads.

Observing the Brain: Neuroimaging Basics

Explores neuroimaging basics, brain network scales, connectivity, history, and physics, emphasizing the importance of understanding data at different scales.

Excel Upgrade: Advanced Functions and Data Analysis

Covers advanced Excel functions and data analysis techniques, including automatic recording and using Solver.

Data Mining: Introduction Log in to Mediaspace to watch this video

Covers the challenges and opportunities of data mining, practical questions, algorithm components, and applications like shopping basket analysis.

Neuroscience Data Analysis Log in to Mediaspace to watch this video

Explores neuroscience data analysis, emphasizing structured data, computational tools, and the trend of computational neuroscience as a service.

Data-Driven Modeling in Neuroscience: Meenakshi Khosla Log in to Mediaspace to watch this video

By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.