Viscioletti.it – La fabbrica delle idee
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IBM Q2 2024 Earnings Call Summary
The IBM Q2 2024 earnings call reported strong financial results, demonstrating solid revenue growth, increased profitability, and significant cash-flow generation. Below are the key highlights from the earnings call: Financial Highlights: IBM Q2 2024 Key Financial Metrics Metric Q2 2024 Year-over-Year Growth Revenue $15.8 billion +4% Operating Pre-tax Income $2.8 billion +17% Operating Diluted EPS…
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I am loving Gradio, discover it with me
Introduction to Gradio Lite and Its Applications I discovered Gradio by reading a book regarding Kaggle competition, that by the way I totally recommend for whoever wants to improve their skills as a data scientist. I played a bit with it at the beginning, but then I couldn’t find a way I just discovered that…
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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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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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