Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Practice
Publications
Startups
Units
Show all results for
Home
Lecture
Linking IoT sensors and cloud
Graph Chatbot
Related lectures (32)
Introduction to Machine Learning: Course Overview and Basics
Introduces the course structure and fundamental concepts of machine learning, including supervised learning and linear regression.
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.
Google Earth Engine: Analyzing Geospatial Data
Introduces Google Earth Engine, focusing on its capabilities for geospatial analysis and environmental monitoring.
Taxi Trajectory Management
Covers the implementation of an information system for managing taxi trajectories, including filtering data, creating trajectory models, and comparing performance.
Data Journalism: Techniques and Examples
Delves into the fundamentals of data journalism and showcases its impact through real-world examples from The Pudding and The Guardian.
Data Visualization: Techniques and Applications
Explores data visualization techniques, design impact, and interactive applications for effective information communication.
Introduction to Spark Runtime Architecture
Covers the Spark runtime architecture, including RDDs, transformations, actions, and caching for performance optimization.
NABEL Data Analysis
Covers the NABEL Data Analysis Assignment, emphasizing data analysis skills and report formatting for air pollution concentrations and meteorology.
Introduction to Machine Learning
Covers the basics of machine learning, including supervised and unsupervised learning, linear regression, and classification.
Big Data: Best Practices and Guidelines
Covers best practices and guidelines for big data, including data lakes, typical architecture, challenges, and technologies used to address them.
Unsupervised Learning: Dimensionality Reduction and Clustering
Covers unsupervised learning, focusing on dimensionality reduction and clustering, explaining how it helps find patterns in data without labels.
Data Science for Engineers: Part 2
Explores data manipulation, exploration, and visualization in data science projects using Python.
Previous
Page 2 of 2
Next