Using SCITAS Clusters

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (32)

Page 3 of 4

Python Programming: File Handling and Exceptions

Explores file handling and exceptions in Python programming, covering reading, writing, and error handling strategies.

Real-Time Control Systems: Determinism and Automation

Explores real-time control systems, determinism, and automation in critical systems, emphasizing the significance of meeting time constraints for safety and efficiency.

Clustering: k-means

Explains k-means clustering, assigning data points to clusters based on proximity and minimizing squared distances within clusters.

Threads and Locks

Explores threads in programming, shared data challenges, locks, and thread management in graphical interfaces and web applications.

Advanced Pandas Functions

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

Decision Tree Classification

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

Machine Learning: Supervised and Unsupervised Learning Techniques

Covers supervised and unsupervised learning techniques in machine learning, highlighting their applications in finance and environmental analysis.

Recursive Functions: Examples and Applications

Explores recursive functions, including factorials and Fibonacci sequences, and their scope and namespaces.

Unsupervised Learning: Clustering Methods

Explores unsupervised learning through clustering methods like K-means and DBSCAN, addressing challenges and applications.

Big Data Ecosystems: Technologies and Challenges

Covers the fundamentals of big data ecosystems, focusing on technologies, challenges, and practical exercises with Hadoop's HDFS.