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Data Workflows in Football Analytics: From Questions to Insights

Data Science Dojo

Typically, datasets can have errors, missing values, or inconsistencies, so ensuring your data is clean and well-structured is essential for accurate analysis. Data profiling helps identify issues such as missing values, duplicates, or outliers. Different types of models can help analyze different aspects and predict outcomes.

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Automate mortgage document fraud detection using an ML model and business-defined rules with Amazon Fraud Detector: Part 3

AWS Machine Learning Blog

In the first post of this three-part series, we presented a solution that demonstrates how you can automate detecting document tampering and fraud at scale using AWS AI and machine learning (ML) services for a mortgage underwriting use case. Data must reside in Amazon S3 in an AWS Region supported by the service.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. and Pandas or Apache Spark DataFrames.

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How to Build ETL Data Pipeline in ML

The MLOps Blog

From data processing to quick insights, robust pipelines are a must for any ML system. Often the Data Team, comprising Data and ML Engineers , needs to build this infrastructure, and this experience can be painful. However, efficient use of ETL pipelines in ML can help make their life much easier.

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Elevate Your Data Quality: Unleashing the Power of AI and ML for Scaling Operations

Pickl AI

How to Scale Your Data Quality Operations with AI and ML: In the fast-paced digital landscape of today, data has become the cornerstone of success for organizations across the globe. Every day, companies generate and collect vast amounts of data, ranging from customer information to market trends.

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

ODSC - Open Data Science

Its goal is to help with a quick analysis of target characteristics, training vs testing data, and other such data characterization tasks. Apache Superset GitHub | Website Apache Superset is a must-try project for any ML engineer, data scientist, or data analyst.

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Monitoring Machine Learning Models in Production

Heartbeat

Many tools and techniques are available for ML model monitoring in production, such as automated monitoring systems, dashboarding and visualization, and alerts and notifications. Learn more about building effective ML teams with our free ebook. Data profiling can help identify issues, such as data anomalies or inconsistencies.