Remove Data Mining Remove Deep Learning Remove Predictive Analytics
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Predictive analytics vs. AI: Why the difference matters in 2023?

Data Science Dojo

Artificial Intelligence (AI) and Predictive Analytics are revolutionizing the way engineers approach their work. This article explores the fascinating applications of AI and Predictive Analytics in the field of engineering. Descriptive analytics involves summarizing historical data to extract insights into past events.

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Predictive Analytics: 4 Primary Aspects of Predictive Analytics

Smart Data Collective

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. The applications of predictive analytics are extensive and often require four key components to maintain effectiveness. Data Sourcing.

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Was ist eine Vektor-Datenbank? Und warum spielt sie für AI eine so große Rolle?

Data Science Blog

Vektor-Datenbanken sind ein weiterer Typ von Datenbank, die unter Einsatz von AI (Deep Learning, n-grams, …) Wissen in Vektoren übersetzen und damit vergleichbarer und wieder auffindbarer machen. Diese Funktion der Datenbank spielt seinen Vorteil insbesondere bei vielen Dimensionen aus, wie sie Text- und Bild-Daten haben.

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How to tackle lack of data: an overview on transfer learning

Data Science Blog

1, Data is the new oil, but labeled data might be closer to it Even though we have been in the 3rd AI boom and machine learning is showing concrete effectiveness at a commercial level, after the first two AI booms we are facing a problem: lack of labeled data or data themselves.

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Top 10 Machine Learning (ML) Tools for Developers in 2023

Towards AI

Offering features like TensorBoard for data visualization and TensorFlow Extended (TFX) for implementing production-ready ML pipelines, TensorFlow stands out as a comprehensive solution for both beginners and seasoned professionals in the realm of machine learning.

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Skills Required for Data Scientist: Your Ultimate Success Roadmap

Pickl AI

Mastering programming, statistics, Machine Learning, and communication is vital for Data Scientists. A typical Data Science syllabus covers mathematics, programming, Machine Learning, data mining, big data technologies, and visualisation. What does a typical Data Science syllabus cover?

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Introducing the Topic Tracks for ODSC East 2024?—?Highlighting Gen AI, LLMs, and Responsible AI

ODSC - Open Data Science

NLP and LLMs The NLP and LLMs track will give you the opportunity to learn firsthand from core practitioners and contributors about the latest trends in data science languages and tools, such as pre-trained models, with use cases focusing on deep learning, speech-to-text, and semantic search.