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Creating an artificial intelligence 101

Dataconomy

How to create an artificial intelligence? The creation of artificial intelligence (AI) has long been a dream of scientists, engineers, and innovators. With advances in machine learning, deep learning, and natural language processing, the possibilities of what we can create with AI are limitless.

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Generative vs Discriminative AI: Understanding the 5 Key Differences

Data Science Dojo

In the recent discussion and advancements surrounding artificial intelligence, there’s a notable dialogue between discriminative and generative AI approaches. These algorithms use existing data like text, images, and audio to generate content that looks like it comes from the real world. What is Generative AI?

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How do I choose a machine learning algorithm for my application?

Mlearning.ai

Photo by Andy Kelly on Unsplash Choosing a machine learning (ML) or deep learning (DL) algorithm for application is one of the major issues for artificial intelligence (AI) engineers and also data scientists. Explore algorithms: Research and explore different algorithms that are desired for your problem.

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How to Choose the Best Algorithm for Your Machine Learning Project

Mlearning.ai

However, with a wide range of algorithms available, it can be challenging to decide which one to use for a particular dataset. In this article, we will discuss some of the factors to consider while selecting a classification & Regression machine learning algorithm based on the characteristics of the data.

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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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Are AI technologies ready for the real world?

Dataconomy

Artificial intelligence, one of the most talked about topics in today’s technology world, has played a huge role in bringing many things into our lives, especially in the last five years. But does that mean artificial intelligence is perfect? The next critical step is model selection.

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2024 Tech breakdown: Understanding Data Science vs ML vs AI

Pickl AI

Summary: In the tech landscape of 2024, the distinctions between Data Science and Machine Learning are pivotal. Data Science extracts insights, while Machine Learning focuses on self-learning algorithms. Markets for each field are booming, offering diverse job roles, especially in Machine Learning for Data Analytics.