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A Guide to Exploratory Data Analysis Explained to a 13-year-old!

Analytics Vidhya

Introduction You might be wandering in the vast domain of AI, and may have come across the word Exploratory Data Analysis, or EDA for short. The post A Guide to Exploratory Data Analysis Explained to a 13-year-old! Well, what is it? Is it something important, if yes why? appeared first on Analytics Vidhya.

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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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Practicing Machine Learning with Imbalanced Dataset

Analytics Vidhya

Introduction In today’s world, machine learning and artificial intelligence are widely used in almost every sector to improve performance and results. But are they still useful without the data? The machine learning algorithms heavily rely on data that we feed to them. The answer is No.

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Unleash Your Data Insights: Learn from the Experts in Our DataHour Sessions

Analytics Vidhya

Introduction Analytics Vidhya DataHour is designed to provide valuable insights and knowledge to individuals looking to build a career in the data-tech industry. These sessions cover a wide range of topics, from the fields of artificial intelligence, and machine learning, and various topics related to data science.

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Exploring Different Types of Data Analysis: Methods and Applications

Pickl AI

Summary: This article explores different types of Data Analysis, including descriptive, exploratory, inferential, predictive, diagnostic, and prescriptive analysis. Introduction Data Analysis transforms raw data into valuable insights that drive informed decisions. What is Data Analysis?

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Artificial Intelligence Using Python: A Comprehensive Guide

Pickl AI

Summary: This guide explores Artificial Intelligence Using Python, from essential libraries like NumPy and Pandas to advanced techniques in machine learning and deep learning. It equips you to build and deploy intelligent systems confidently and efficiently.

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LLMOps demystified: Why it’s crucial and best practices for 2023

Data Science Dojo

Some projects may necessitate a comprehensive LLMOps approach, spanning tasks from data preparation to pipeline production. Exploratory Data Analysis (EDA) Data collection: The first step in LLMOps is to collect the data that will be used to train the LLM. Why is LLMOps Essential?