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Loan Approval Prediction Machine Learning

Analytics Vidhya

Introduction In this article, we are going to solve the Loan Approval Prediction Hackathon hosted by Analytics Vidhya. classification refers to a predictive modeling problem where a class label is predicted for a given example of […].

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Why you should care about debugging machine learning models

O'Reilly on Data

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing problems in ML models, is so critical to the future of ML.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is machine learning? This post will dive deeper into the nuances of each field.

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15 best data science bootcamps for boosting your career

CIO Business Intelligence

The data science path you ultimately choose will depend on your skillset and interests, but each career path will require some level of programming, data visualization, statistics, and machine learning knowledge and skills. It offers a bootcamp in data science and machine learning for individuals with experience in Python and coding.

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Reflections on the Knowledge Graph Conference 2023

Ontotext

The event attracts individuals interested in graph technology, machine learning and natural language processes in numerous verticals, including publishing, government, financial services, manufacturing and retail. During the conference, the organizers hosted a separate track called the Healthcare and Life Sciences Symposium.

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What to Do When AI Fails

O'Reilly on Data

And last is the probabilistic nature of statistics and machine learning (ML). Most AI models decay overtime: This phenomenon, known more widely as model decay , refers to the declining quality of AI system results over time, as patterns in new data drift away from patterns learned in training data.

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Announcing the 2021 Data Impact Awards

Cloudera

2020 saw us hosting our first ever fully digital Data Impact Awards ceremony, and it certainly was one of the highlights of our year. Use cases could include but are not limited to: predictive maintenance, log data pipeline optimization, connected vehicles, industrial IoT, fraud detection, patient monitoring, network monitoring, and more.