Predicting Bitcoin's Price with ML and Twitter Inputs

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Apache Spark Ecosystem: Basics and Operations

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

Acquiring Data for Learning

Explores training robots through reinforcement learning and learning from demonstration, highlighting challenges in human-robot interaction and data collection.

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.

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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.

Machine Learning Fundamentals

Covers the fundamental principles and methods of machine learning, including supervised and unsupervised learning techniques.

Interview Methods

Explores interview survey methods, preparation, types of interviews, question formulation, and interaction quality.

Water Consumption in Geneva

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

Introduction to Machine Learning: Basics and Examples

Introduces the basics of machine learning, covering supervised learning, reinforcement learning, and dimension reduction.

Generative AI: EPFL Project

Introduces an EPFL project on generative AI advancements and training engineers in large-scale AI systems.