Category: AI
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Autonomous Vehicles and Us: Love/Hate Story
Autonomous vehicles have transitioned from being a off vision, to an approaching reality thanks to the integration of AI technology. These self driving cars hold the promise of transforming transportation as we know it. Recently a thought provoking Twitter thread piqued my interest in how AI’s propelling this journey forward. Lets delve into the workings…
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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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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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Empower Your Projects: Building the Future with ChatGPT’s PromptGPT—A Breakthrough in App Development
This article explores how I turned an idea into a web app in one day, using HTML, CSS, and JavaScript. Discover how ChatGPT streamlines making web apps, making easier web development for everyone.
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Peak Performance Modeling: Harnessing Bagging and Boosting for Superior Results
In the world of machine learning, two key ensemble techniques stand out. They can improve model performance. They are: bagging and boosting. But how do you decide which one to use? Let’s break it down.
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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…
