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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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Practicing Machine Learning with Imbalanced Dataset

Analytics Vidhya

The machine learning algorithms heavily rely on data that we feed to them. The quality of data we feed to the algorithms […] The post Practicing Machine Learning with Imbalanced Dataset appeared first on Analytics Vidhya. But are they still useful without the data? The answer is No.

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The ultimate guide to the Machine Learning Model Deployment

Data Science Dojo

Getting your ML model ready for action: This stage involves building and training a machine learning model using efficient machine learning algorithms. Exploratory data analysis (EDA): EDA is a process of exploring data to gain insights into its distribution, relationships, and patterns.

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Ending an Ugly Chapter in Chip Design

Flipboard

The crux of the clash was whether Google’s AI solution to one of chip design’s thornier problems was really better than humans or state-of-the-art algorithms. It pitted established male EDA experts against two young female Google computer scientists, and the underlying argument had already led to the firing of one Google researcher.

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11 Open Source Data Exploration Tools You Need to Know in 2023

ODSC - Open Data Science

ydata-profiling GitHub | Website The primary goal of ydata-profiling is to provide a one-line Exploratory Data Analysis (EDA) experience in a consistent and fast solution. Algorithm-visualizer GitHub | Website Algorithm Visualizer is an interactive online platform that visualizes algorithms from code.

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Unraveling the phenomenon of ChatGPT: Understanding the revolutionary AI technology 

Data Science Dojo

Want to start your EDA journey, well you can always get yourself registered at Data Science Bootcamp. By using auto chat, companies can reduce wait times, improve response accuracy and provide a more personalized customer experience.

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

Data Science Dojo

Exploratory Data Analysis (EDA) Data collection: The first step in LLMOps is to collect the data that will be used to train the LLM. This is done by using a machine learning algorithm to learn the patterns in the data. The scope of LLMOps within machine learning projects can vary widely, tailored to the specific needs of each project.