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An Exploratory Data Analysis Guide for Beginners

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction on Exploratory Data Analysis When we start with data science we all want to dive in and apply some cool sounding algorithms like Naive Bayes, XGBoost directly to our data and expects to get some magical results.

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Exploratory Data Analysis (EDA) – Credit Card Fraud Detection Case Study

Analytics Vidhya

Overview Lots of financial losses are caused every year due to credit card fraud transactions, the financial industry has switched from a posterior investigation approach to an a priori predictive approach with the design of fraud detection algorithms to warn and help fraud investigators. […].

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Linear regression

Dataconomy

Understanding supervised learning In supervised learning, algorithms learn from training data that includes input-output pairs. Advantages of using linear regression Linear regression has several benefits, including: Its a straightforward method, facilitating exploratory data analysis.

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The ultimate guide to the Machine Learning Model Deployment

Data Science Dojo

The development of a Machine Learning Model can be divided into three main stages: Building your ML data pipeline: This stage involves gathering data, cleaning it, and preparing it for modeling. For data scrapping a variety of sources, such as online databases, sensor data, or social media.

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Empower your career – Discover the 10 essential skills to excel as a data scientist in 2023

Data Science Dojo

Ability to apply math and statistics appropriately Exploratory data analysis is a crucial step in the data science process, as it allows data scientists to identify important patterns and relationships in the data, and to gain insights that inform decisions and drive business growth.

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Journeying into the realms of ML engineers and data scientists

Dataconomy

Their expertise lies in designing algorithms, optimizing models, and integrating them into real-world applications. The rise of machine learning applications in healthcare Data scientists, on the other hand, concentrate on data analysis and interpretation to extract meaningful insights.

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Data Science Dojo - Untitled Article

Data Science Dojo

It could explain how these distributions are used in different machine learning algorithms and why understanding them is crucial for data scientists. 32 datasets to uplift your skills in data science Data Science Dojo has created an archive of 32 data sets for you to use to practice and improve your skills as a data scientist.