Machine Learning in IoT Era: Interview with Philippe Ryvlin

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Excel Upgrade: Advanced Functions and Data Analysis

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

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

Apache Spark Ecosystem: Basics and Operations

Provides an overview of the Apache Spark ecosystem, covering basics, operations, and key components.

Socially-aware Artificial Intelligence for Last-mile Mobility

Explores socially-aware AI for last-mile mobility, focusing on understanding social etiquettes, anticipating behaviors, and forecasting crowd movements.

Introduction to Data Stream Processing: Concepts and Applications

Covers the principles of data stream processing and its applications in real-time data analysis.

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.

Water Consumption in Geneva

Explores water consumption data in Geneva, including charts on consumption and losses, available datasets, and data processing phases.

Neural Networks: Training and Activation

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Unsupervised Learning: Clustering & Dimensionality Reduction

Introduces unsupervised learning through clustering with K-means and dimensionality reduction using PCA, along with practical examples.

Advanced Spark Optimization Techniques: Managing Big Data

Discusses advanced Spark optimization techniques for managing big data efficiently, focusing on parallelization, shuffle operations, and memory management.