Machine Learning

This section of my blog focus on using Machine Learning Methods for data science. I discuss various Machine Learning algorithms that I have been using during my career.

Exploring Cargo: A Comprehensive Guide to RUST’s Package Manager

RUST, a systems programming language known for its focus on safety, performance, and concurrency, comes equipped with a powerful package manager called Cargo. In this article, we delve into the intricacies of Cargo, exploring its role in building, deploying, and managing dependencies in RUST projects. Through practical code examples, we will unravel the functionalities of …

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Unleashing the Power of RUST: A Guide for Data Scientists

In the ever-evolving landscape of programming languages, one contender has been gaining significant attention for its unique blend of performance and safety: the RUST programming language. This article aims to delve into the intricacies of RUST, exploring its fundamentals, its utility in comparison to Python and other lower-level languages, and how data scientists can harness …

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Retrieval Augmented Generation (RAG): A Primer for Data Scientists

Retrieval augmented generation (RAG) is an exciting new paradigm in natural language processing that combines the powers of neural retrieval and neural text generation. For data scientists, RAG opens up new possibilities for building AI systems that can generate high-quality, knowledge-grounded text.   In RAG, a retriever module first searches over a large corpus to …

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Embracing the Future: The Enduring Significance of Insight Analysts and Data Scientists in an AI-Transformed World (Worlds of ChatGPT and Bard)

In an age where artificial intelligence (AI) and Large Language Models (for example ChatGPT and Bard) are driving efficiency, leveraging specialised data, and ushering in an era of hyper development, the roles of insight analysts and data scientists are more critical than ever. These technologies have the potential to replace certain skills, such as code …

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Data-Driven Insights: Writing Reports and Presenting Data with Power BI and Tableau

In the age of data, the ability to effectively communicate insights is just as crucial as the research itself. As researchers harness the power of machine learning (ML) and data science, presenting data in a compelling and accessible manner becomes paramount. In this article, we delve into the art of conveying data-driven insights through comprehensive …

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Python and SQL vs. SPSS: Empowering Researchers with Open-Source Versatility

In the world of research, the choice of tools can significantly impact the efficiency and effectiveness of data analysis. Traditionally, researchers have relied on proprietary software like SPSS for statistical analysis. However, a transformative shift is underway, as open-source technologies like Python and SQL are gaining momentum, offering cost-effective and versatile solutions. In this article, …

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Panel Research: A Dynamic Approach to Longitudinal Studies

In the realm of research, understanding how phenomena evolve over time is essential for making informed decisions and strategic planning. Conventional methods may provide valuable insights, but they often lack the dynamism required to track changes, behaviours, and trends over extended periods. Enter panel research, a dynamic approach supercharged by machine learning (ML) algorithms that …

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Normalisation Indexes: The Key to Data Comparability

In the data-driven realm of research, harnessing the power of vast and diverse datasets can be both a boon and a challenge. As researchers, ensuring comparability and coherence across data points is crucial to drawing meaningful insights. The art of normalisation, often considered an enigma, is the key to creating standardised indexes that enable seamless …

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Web Scraping for Real-Time Intelligence

In the ever-evolving landscape of research, staying ahead of the competition requires access to real-time intelligence. Conventional data collection methods may not always provide the timeliness required to make agile and informed decisions. However, on this transformative journey of machine learning (ML) and data science, we encounter web scraping—a formidable tool that unlocks dynamic and …

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Data Fusion: The Convergence of Information

In the vast landscape of research, information resides in various forms and sources. Conventional approaches to data analysis often involve examining individual datasets in isolation, limiting the depth of insights and overlooking valuable relationships.   However, in this transformative era of machine learning (ML) and data science, the concept of data fusion emerges as a …

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