Tag: data science
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Love this Guide to Learning to Rank: RankNet, LambdaRank, and ListNet Explained
Hey there, data enthusiasts! we’re diving into the fascinating world of Learning to Rank (LTR) methods—a crucial machine learning tool in the realm of information retrieval. Whether you’re a seasoned data scientist or just starting out, understanding LTR can significantly enhance your ability to provide users with the most relevant search results. Let’s break it…
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AI Made Easy: Decision Trees for Data Science Success
In the world of Data Science and AI, it’s exciting to discover that sometimes even simple algorithms can help make sense of complex datasets. Imagine a world where you make decisions with the help of Decision Trees!
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How to Handle Missing Data in Machine Learning (Part 1)
Introduction In the world of data science, missing data is a common issue that can impact the performance of machine learning models. In data scientist job interviews, I often ask candidates how they would handle missing data in a machine learning project. Surprisingly, many struggle to choose the most appropriate method. This article explores various…
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How to Handle Missing Data in Machine Learning (Part 2)
Introduction In this part, I’ll walk you through a practical example about how to handle missing data using a dataset with missing values. I will show different imputation techniques and discuss their impacts. Practical Examples Let’s walk through a practical example using a dataset with missing values. We will demonstrate different imputation techniques and discuss…
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3 Proven Real-World Data Science Strategies for Success
As a data scientist, I’ve faced many challenges throughout the years. While working on various projects, I’ve learned some key strategies through trial and error. They have greatly improved my workflow and the effectiveness of the solutions. Learning these lessons involved a fair share of pain. So, if you are a junior data scientist entering…
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Customer Reviews Forensics: An Approach To Stunning Expert Insights
Customer Reviews: Why They Matter In a competitive market understanding customer reviews is crucial for enhancing product offerings and customer satisfaction. This article outlines an analysis of user reviews from a leading software provider, focusing on methodological approaches to dissect user sentiment and providing strategic recommendations. The Data Source The dataset used for this analysis…
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How Amazon Bedrock improved speed in LLM testing
This article is about Amazon Bedrock and its value proposition in the LLM arena. Using this tool, I tested different LLMs for a text classification task.
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Elevate Data Analysis: The Ultimate Pandas Guide to Conditional Columns
In this article, discover an easy Pandas trick: Create conditional columns. You can create new columns in your DataFrame using this trick. Conditions applied to existing data serve as the basis for the new columns. It’s useful for feature engineering, data cleaning, or preparing data. Use it for analysis or modelling tasks.
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How to handle pull requests in git and GitHub
Software development is changing. Mastering pull requests in Git and GitHub is like learning diplomacy in coding. This article starts aims to explain the details of this art. It presents a guide for both the raiser and the reviewer. At its core, the process is a delicate balance. It is about proposing improvements in a…
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Decision Trees in a Nutshell: A ‘Statistics in Pills’ Perspective
Welcome to “Statistics in Pills.” We simplify complex machine learning concepts into bite-sized, easy-to-understand insights. Today’s topic is the fascinating Decision Trees algorithm. It is a fundamental tool in machine learning. It plays a crucial role in the field. Understanding Decision Trees: The Simplicity Behind Complexity Picture a tree, not one that you find in…
