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How to get datasets for Machine Learning?

Knowledge Hut

Open Dataset Finders To solve any problem in data science, be it in the field of Machine Learning, Deep Learning, or Artificial Intelligence , one needs a dataset that can be input into the model to derive insights. A technology has no significance without data. The datasets for Deep Learning are as follows.

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Pattern Recognition in Machine Learning [Basics & Examples]

Knowledge Hut

This can be done by finding regularities in the data, such as correlations or trends, or by identifying specific features in the data. Pattern recognition is used in a wide variety of applications, including Image processing, Speech recognition, Biometrics, Medical diagnosis, and Fraud detection.

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Deep Learning vs Machine Learning: What’s The Difference?

Knowledge Hut

On that note, let's understand the difference between Machine Learning and Deep Learning. Below is a thorough article on Machine Learning vs Deep Learning. We will see how the two technologies differ or overlap and will answer the question - What is the difference between machine learning and deep learning?

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Audio Analysis With Machine Learning: Building AI-Fueled Sound Detection App

AltexSoft

Aiming at understanding sound data, it applies a range of technologies, including state-of-the-art deep learning algorithms. Audio Toolbox by MathWorks offers numerous instruments for audio data processing and analysis, from labeling to estimating signal metrics to extracting certain features. Audio data analysis steps.

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Top 16 Data Science Specializations of 2024 + Tips to Choose

Knowledge Hut

Professionals from a variety of disciplines use data in their day-to-day operations and feel the need to understand cutting-edge technology to get maximum insights from the data, therefore contributing to the growth of the organization. Some Deep Learning frameworks include TensorFlow, Keras, and PyTorch.

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Data Science Learning Path [Beginners Roadmap]

Knowledge Hut

Understanding what defines data in the modern world is the first step toward the Data Science self-learning path. There is a much broader spectrum of things out there which can be classified as data. For some, it does not matter what the data is about.

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Data Pipelines in the Healthcare Industry

DareData

The Challenges of Medical Data In recent times, there have been several developments in applications of machine learning to the medical industry. Odds are that your local hospital, pharmacy or medical institution's definition of being data-driven is keeping files in labelled file cabinets, as opposed to one single drawer.