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Using KNIME for Data Driven Decision Making

Analytics Vidhya

Introduction In 2017, The Economist declared that “the world’s most valuable resource is no longer oil, but data.” Companies like Google, Amazon, and Microsoft gather large bytes of data, harvest it, and create complex tracking algorithms. This article was published as a part of the Data Science Blogathon.

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The effectiveness of clustering in IIoT

Mlearning.ai

How this machine learning model has become a sustainable and reliable solution for edge devices in an industrial network An Introduction Clustering (cluster analysis - CA) and classification are two important tasks that occur in our daily lives. 3 feature visual representation of a K-means Algorithm.

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We still have so much to learn from nature

Dataconomy

The Kilobot platform provides researchers with a practical means to study and experiment with swarm robotics algorithms and concepts. Swarm intelligence algorithms are typically decentralized, meaning that they do not require a central controller. The robots were able to plant the rice more quickly and efficiently than human workers.

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From Rulesets to Transformers: A Journey Through the Evolution of SOTA in NLP

Mlearning.ai

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. NLP algorithms help computers understand, interpret, and generate natural language.

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A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

The following figure illustrates the idea of a large cluster of GPUs being used for learning, followed by a smaller number for inference. In 2017, the landmark paper “ Attention is all you need ” was published, which laid out a new deep learning architecture based on the transformer.

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How LotteON built a personalized recommendation system using Amazon SageMaker and MLOps

AWS Machine Learning Blog

Therefore, we decided to introduce a deep learning-based recommendation algorithm that can identify not only linear relationships in the data, but also more complex relationships. Recommendation model using NCF NCF is an algorithm based on a paper presented at the International World Wide Web Conference in 2017.

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Tuning Word2Vec with Bayesian Optimization: Applied to Music Recommendations

Towards AI

Word2Vec, a widely-adopted NLP algorithm has proven to be an efficient and valuable tool that is now applied across multiple domains, including recommendation systems. Songs that frequently co-occur or appear in similar contexts will have vector representations that are clustered closer together in the high-dimensional embedding space.