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Fraud Detection using Deep Learning

Cloudera

The approach to machine learning using deep learning has brought marked improvements in the performance of many machine learning domains and it can apply just as well to fraud detection. The research team at Cloudera Fast Forward have written a report on using deep learning for anomaly detection.

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How to get datasets for Machine Learning?

Knowledge Hut

Datasets are the repository of information that is required to solve a particular type of problem. Also called data storage areas , they help users to understand the essential insights about the information they represent. Datasets play a crucial role and are at the heart of all Machine Learning models.

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Natural Language Processing: A Guide to NLP Use Cases, Approaches, and Tools

AltexSoft

But today’s programs, armed with machine learning and deep learning algorithms, go beyond picking the right line in reply, and help with many text and speech processing problems. You can’t simply feed the system your whole dataset of emails and expect it to understand what you want from it. Preparing an NLP dataset.

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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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NVIDIA RAPIDS in Cloudera Machine Learning

Cloudera

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. To try and predict this, an extensive dataset including anonymised details on the individual loanee and their historical credit history are included. Get the Dataset.

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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. For further steps, you need to load your dataset to Python or switch to a platform specifically focusing on analysis and/or machine learning. Labeling of audio data in Audacity.

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Pattern Recognition in Machine Learning [Basics & Examples]

Knowledge Hut

Data analysis and Interpretation: It helps in analyzing large and complex datasets by extracting meaningful patterns and structures. By identifying and understanding patterns within the data, valuable insights can be gained, leading to better decision-making, and understanding of underlying relationships.