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📝 Latest Posts

Is Data Science Dying in 2024? Unraveling the Transformation

Exploring the evolution and potential decline of the data science field in 2024, as technology advances reshape its landscape.

Transitioning from Model-Centric to Data-Driven Data Science in Business

An in-depth exploration of the shift from model-centric to data-driven data science in businesses, examining the current landscape, future prospects, and strategies for…

Embracing the Cloud: The Future of Data Ecosystems

Exploring the evolution and future trends in cloud data ecosystems, focusing on their impact on data management and analytics in 2023 and beyond.

📚 Latest Courses

Next Course: Coming Soon

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Applied Graph Theory with Python

This course offers a deep dive into Graph Theory, tailored for data scientists, programmers, and computer science students.

📔 Latest Notebooks

Confidence Levels: Exploring Probabilities in Explainable Large Language Models

In this blog post, we delve into the inner workings of large language models (LLMs) and explore a novel approach to enhancing their explainability. By visualizing the probabilities associated with each generated word, we aim to gain insights into the model’s confidence levels and understand how they might impact the overall quality of the generated text. This research-oriented exploration not only sheds light on the decision-making process of LLMs but also paves the way for more transparent and trustworthy natural language generation systems.

LLMs: Embeddings to Text

In this short notebook we are exploring the capabilities of a relativly new concept called Text Embeddings Reveal

Analysing Social Networks

Analysing Social Networks using the Facebook Social Circles Dataset and the NetworkX Python library.