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Deep learning model to predict mRNA Degradation

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Designing a deep learning model that will predict degradation rates at each base of an RNA molecule using the Eterna dataset comprising over 3000 RNA molecules.

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Pneumonia Prediction: A guide for your first CNN project

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Deep Learning is a very powerful tool that has now. The post Pneumonia Prediction: A guide for your first CNN project appeared first on Analytics Vidhya.

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What is predictive analytics? Transforming data into future insights

CIO Business Intelligence

With the help of sophisticated predictive analytics tools and models, any organization can now use past and current data to reliably forecast trends and behaviors milliseconds, days, or years into the future. Predictive analytics has captured the support of wide range of organizations, with a global market size of $12.49

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The quest for high-quality data

O'Reilly on Data

Even if we boosted the quality of the available data via unification and cleaning, it still might not be enough to power the even more complex analytics and predictions models (often built as a deep learning model). Machine learning applications rely on three main components: models, data, and compute.

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Of Muffins and Machine Learning Models

Cloudera

For example, if you need to build a model for customer churn prediction, you can initiate a new churn modelling with scikit-learn project within Cloudera’s management console or via a call to CML’s RESTful API service. This might require making batch and individual predictions.

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AI In Analytics: Today and Tomorrow!

Smarten

The use of Generative AI, LLM and products such as ChatGPT capabilities has been applied to all kinds of industries, from publishing and research to targeted marketing and healthcare. Nothing…and I DO mean NOTHING…is more prominent in technology buzz today than Artificial Intelligence (AI). billion, with the market growing by 31.1%

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Proposals for model vulnerability and security

O'Reilly on Data

The objective here is to brainstorm on potential security vulnerabilities and defenses in the context of popular, traditional predictive modeling systems, such as linear and tree-based models trained on static data sets. If an attacker can receive many predictions from your model API or other endpoint (website, app, etc.),

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