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As a data scientist, Jupyter Notebook has become one of the first platforms we learn to use, as it allows for easier data manipulation compared to standard programming IDEs. Given its utility, Jupyter Notebook has become a standard tool that every data scientist now uses in their daily work.
Jupyter Notebook…
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"AI agents will become an integral part of our daily lives, helping us with everything from scheduling appointments to managing our finances. They will make our lives more convenient and efficient." —Andrew Ng
After the growing popularity of large language models (LLMs), the next…
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When it comes to error handling, the first thing we usually learn is how to use try-except blocks. But is that really enough as our codebase grows more complex? I believe not. Relying solely on try-except can lead to repetitive, cluttered, and hard-to-maintain code.
In this article, I’ll…
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An organization's data teams often encounter complex projects with a variety of resources and structures scattered around. As the number of projects and team members increases, the information becomes more tangled and increasingly complex to manage. This is why we need to consolidate the information in a single platform.…
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Machine learning (ML) algorithms are key to building intelligent models that learn from data to solve a particular task, namely making predictions, classifications, detecting anomalies, and more. Optimizing ML models entails adjusting the data and the algorithms that lead to building such models, to achieve more accurate and efficient results, and…
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In a previous article, I explained how AI is the skill of the future, with roles that command salaries up to $375,000 annually.
Large Language Models (LLMs) have become a central focus in AI, and almost every data-centric role now requires some foundational understanding of these algorithms.
Whether you’re a developer…
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With the emergence of large language models, prompt engineering has become an essential skill. Put simply, prompting involves how humans interact with machines. Engineering the prompt suggests an effective way to communicate the requirement so that the machines’ responses are contextual, relevant, and accurate.
The Framework
The…
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Machine Learning (ML for short) is not just about making predictions. There are other unsupervised processes, among which clustering stands out. This article introduces clustering and cluster analysis, highlighting the potential of cluster analysis for segmenting, analyzing, and gaining insights from groups of similar data
What is Clustering?
In…
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Learning how to code is learning a new language. Although you can learn it by yourself, it makes it 10 times easier when you have a teacher or a course outline to follow. Python is one of the most popular programming languages due to its simplicity.
For…
Inception of LLMs - NLP and Neural Networks
The creation of Large Language Models didn’t happen overnight. Remarkably, the first concept of language models started with rule-based systems dubbed Natural Language Processing. These systems follow predefined rules that make decisions and infer conclusions based on text input. These systems rely on if-else statements…