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Data exploration

Dataconomy

Exploratory data analysis (EDA) Exploratory Data Analysis (EDA) is a systematic approach within the data exploration framework. Audience targeting and productivity: Transforming raw data into meaningful stories allows organizations to connect with their audience better, enhancing overall productivity and outcomes.

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

Towards AI

Table of Contents Environment Setup Dataset Overview Preprocessing and Tokenization Exploratory Data Analysis (EDA) Training and Fine-Tuning Evaluating the Model Conclusion and Key Takeaways Environment Setup We will use the Hugging Face Transformers library, which offers pre-trained models and tools to fine-tune them. .

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Predicting the 2024 U.S. Presidential Election Winner Using Machine Learning

Towards AI

Target Variable: Party Affiliation: Denotes whether a respondent tends to be a supporter of either the Republic or Democrat party Exploratory Data Analysis (EDA) Analysis A study at the invested high level of exploratory data analysis (EDA) will serve the aim of understanding distributions, relationships, and potential problems in the data.

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Kimi K2: A Deep Dive into Moonshot AI’s Most Powerful Open-Source Agentic Model

Data Science Dojo

Open Source + Cost Efficiency Free access via Kimi’s web/app interface Model weights available on Hugging Face and GitHub Inference compatibility with popular engines like vLLM, TensorRT-LLM, and SGLang API pricing : Much lower than OpenAI and Anthropic—about $0.15 per million input tokens and $2.50

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The Lifecycle of Feature Engineering: From Raw Data to Model-Ready Inputs

Flipboard

Key activities during this phase include: Exploratory Data Analysis (EDA) : Use visualizations and summary statistics to understand distributions, relationships, and anomalies. Understanding Raw Data Raw data contains inconsistencies, noise, missing values, and irrelevant details. Data audit : Identify variable types (e.g.,

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xAI’s Grok 4: A Bold Step Forward in Powerful and Practical AI

Data Science Dojo

of thw problems source: xAI Real-World Use Cases Whether you’re a data scientist, developer, or researcher, Grok 4 opens up a wide range of possibilities: Exploratory Data Analysis : Grok 4 can automate EDA, identify patterns, and suggest hypotheses. Grok 4 was able to solve about 38.6%

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Exploratory data analysis (EDA)

Dataconomy

Exploratory data analysis (EDA) is a critical component of data science that allows analysts to delve into datasets to unearth the underlying patterns and relationships within. EDA serves as a bridge between raw data and actionable insights, making it essential in any data-driven project. What is exploratory data analysis (EDA)?