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Anomaly Detection on Google Stock Data 2014-2022

Analytics Vidhya

In this project, we’ll dive into the historical data of Google’s stock from 2014-2022 and use cutting-edge anomaly detection techniques to uncover hidden patterns and gain insights into the stock market.

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Our brains are vector databases — here’s why that’s helpful when using AI

Flipboard

In 2014, a breakthrough at Google transformed how machines understand language: The self-attention model. This innovation allowed AI to grasp context and meaning in human communication by treating words as mathematical vectors — precise numerical representations that capture relationships between …

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A Basic Guide To Kubernetes in Production

Analytics Vidhya

In 2014, the first echoes of the word Kubernetes in tech were heard, and the conquest of Kubernetes is due in no small amount to its flexibility and authority. This article was published as a part of the Data Science Blogathon. Back […]. The post A Basic Guide To Kubernetes in Production appeared first on Analytics Vidhya.

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TensorFlow and AlphaGo Makers Merged to Form Google DeepMind

Analytics Vidhya

DeepMind is an artificial intelligence (AI) company acquired by Google in 2014. Alphabet, the parent company of Google, has announced that DeepMind will merge with Google’s Brain team to form Google DeepMind. DeepMind CEO Demis Hassabis will head this new collaboration.

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Airflow for Orchestrating REST API Applications

Analytics Vidhya

It started at Airbnb in October 2014 as a solution to manage the company’s increasingly complex workflows. Introduction to Apache Airflow “Apache Airflow is the most widely-adopted, open-source workflow management platform for data engineering pipelines. Most organizations today with complex data pipelines to […].

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Scientists Have Figured Out Why Mysterious Craters Are Popping Up Around Siberia

Extreme Tech

At least 20 massive craters have appeared in Siberia's permafrost since 2014.

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Top 11 Most-asked Interview Questions on GAN Architecture

Analytics Vidhya

It was first proposed in 2014 by Goodfellow as an alternative training methodology to the generative model [1]. Introduction Generative adversarial networks (GANs) are an innovative class of deep generative models that have been developed continuously over the past several years. Since their […].