Remove Deep Learning Remove Internet of Things Remove Natural Language Processing
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Exploring the dynamic fusion of AI and the IoT

Dataconomy

The integration of artificial intelligence in Internet of Things introduces new dimensions of efficiency, automation, and intelligence to our daily lives. Simultaneously, artificial intelligence has revolutionized the way machines learn, reason, and make decisions.

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Predictive analytics vs. AI: Why the difference matters in 2023?

Data Science Dojo

We’ll dive into the core concepts of AI, with a special focus on Machine Learning and Deep Learning, highlighting their essential distinctions. However, with the introduction of Deep Learning in 2018, predictive analytics in engineering underwent a transformative revolution.

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5 Current Trends in Big Data for 2022 and Beyond

Smart Data Collective

Edge computing is processing data at the edge of a network, or on the device itself rather than in a centralized location. The growth in edge computing is mainly due to the increasing popularity of Internet of Things (IoT) devices. The Growth of Natural Language Processing. Strong Reliance On Cloud Storage.

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A Comprehensive Guide on Deep Learning Engineers

Pickl AI

Summary : Deep Learning engineers specialise in designing, developing, and implementing neural networks to solve complex problems. Introduction Deep Learning engineers are specialised professionals who design, develop, and implement Deep Learning models and algorithms.

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Why Data Scale Size Matters When It Comes to Improving Deep Learning Model Stability

ODSC - Open Data Science

Deep learning is one of the most crucial tools for analyzing massive amounts of data. However, there is such a prospect as too much information, as deep learning’s job is to find patterns and connections between data points to inform humanity’s questions and affirm assertions.

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Deep Learning Techniques for Time Series Analysis

Heartbeat

Time series analysis has become increasingly relevant for a variety of industries, including banking, healthcare, and retail, as big data and the internet of things (IoT) have grown in popularity. In this post, we will look at deep learning approaches for time series analysis and how they might be used in real-world applications.

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2021 in Review: What Just Happened in the World of Artificial Intelligence?

Applied Data Science

Initially introduced for Natural Language Processing (NLP) applications like translation, this type of network was used in both Google’s BERT and OpenAI’s GPT-2 and GPT-3. Deepmind has already provided specialisations for reinforcement learning ( rlax ) and graph neural networks ( jraph ). But at what cost?