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Machine Learning in Insurance: Applications, Use Cases, and Projects

ProjectPro

Ever wondered how insurance companies successfully implement machine learning to expand their businesses? Despite its long history of resistance to innovation, the insurance sector is currently experiencing a digital revolution. For both applicants and insurers, this quick move has significant implications.

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Data Collection for Machine Learning: Steps, Methods, and Best Practices

AltexSoft

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

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Biases in Data Collection: Types and How to Avoid the Same

U-Next

In reality, computers, data, and algorithms are not entirely objective. Data analysis can indeed aid in better decision-making, yet bias can still creep in. Similarly, we must consider other data sources while assessing the findings or recommendations of data analysis. . Outliers can severely distort data.

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Future of Data Scientists: Career Outlook

Knowledge Hut

Data Science combines business and mathematics by employing a complex algorithm to the knowledge of the business. Not only in business, but data analysis is also paramount in various fields like predicting disease outbreaks, weather forecasting, recommendations in healthcare, fraud detection, etc.

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Top 15 Power BI Projects To Develop Your Skills in 2024

Edureka

Use DAX for Advanced Calculations : Leverage Data Analysis Expressions (DAX) to create measures and calculated columns that provide deeper insights. Interactive Elements : Add slicers, filters, and other interactive elements to allow users to drill down and explore the data in more detail.

BI 40
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How AI Used in Fraud Detection? Benefits, Techniques, Use cases

Knowledge Hut

Fraud detection with AI and machine learning operates on the principle of learning from data. Here's how it works: Data Collection: The first step is to gather data. This data may contain transaction histories, client information, and past fraud incidents in the context of fraud detection.

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Top 15 Software Engineer Projects 2023 [Source Code]

Knowledge Hut

Personality Analysis System Personality Analysis System project is an exciting software engineering project that requires a good understanding of natural language processing, AI algorithms, and data analysis.