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EDA on SuperStore Dataset Using Python

Analytics Vidhya

Table of Contents Introduction Working with dataset Creating loss dataframe Visualizations Analysis from Heatmap Overall Analysis Conclusion Introduction In this article, I am going to perform Exploratory Data Analysis on the Sample Superstore dataset.

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Fine-Tuning Legal-BERT: LLMs For Automated Legal Text Classification

Towards AI

Performing exploratory data analysis to gain insights into the dataset’s structure. Whether you’re a data scientist aiming to deepen your expertise in NLP or a machine learning engineer interested in domain-specific model fine-tuning, this tutorial will equip you with the tools and insights you need to get started.

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The 6 best ChatGPT plugins for data science 

Data Science Dojo

This means that you can use natural language prompts to perform advanced data analysis tasks, generate visualizations, and train machine learning models without the need for complex coding knowledge. With Code Interpreter, you can perform tasks such as data analysis, visualization, coding, math, and more.

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How Exploratory Data Analysis Helped Me Solve Million-Dollar Business Problems

Towards AI

Photo by Luke Chesser on Unsplash EDA is a powerful method to get insights from the data that can solve many unsolvable problems in business. In the increasingly competitive world, understanding the data and taking quicker actions based on that help create differentiation for the organization to stay ahead!

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Building an End-to-End Machine Learning Project to Reduce Delays in Aggressive Cancer Care.

Towards AI

This article seeks to also explain fundamental topics in data science such as EDA automation, pipelines, ROC-AUC curve (how results will be evaluated), and Principal Component Analysis in a simple way. Act One: Exploratory Data Analysis — Automation The nuisance of repetitive tasks is something we programmers know all too well.

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Exploratory Data Analysis on Stock Market Data

Mlearning.ai

Exploratory Data Analysis on Stock Market Data Photo by Lukas Blazek on Unsplash Exploratory Data Analysis (EDA) is a crucial step in data science projects. It helps in understanding the underlying patterns and relationships in the data. The dataset can be downloaded from Kaggle.

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Control digital voice speech and pitch rate using the Watson Text to Speech (TTS) library

IBM Data Science in Practice

Data Processing and EDA (Exploratory Data Analysis) Speech synthesis services require that the data be in a JSON format. TTS app speech data output Conclusion This blog showed how you could easily use the Watson Speech Library to convert text to speech and control digital speech and pitch rates.