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What are Graph Neural Networks, and how do they work?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Neural Networks have acquired enormous popularity in recent years due to their usefulness and ease of use in the fields of Pattern Recognition and Data Mining.

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What is NLP? Natural language processing explained

CIO Business Intelligence

Lilly Translate uses NLP and deep learning language models trained with life sciences and Lilly content to provide real-time translation of Word, Excel, PowerPoint, and text for users and systems. Licensed by MIT, SpaCy was made with high-level data science in mind and allows deep data mining.

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Non-Generalization and Generalization of Machine learning Models

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction The generalization of machine learning models is the ability of a model to classify or forecast new data. When we train a model on a dataset, and the model is provided with new data absent from the trained set, it may perform […].

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An Important Guide To Unsupervised Machine Learning

Smart Data Collective

With that being said, let’s have a closer look at how unsupervised machine learning is omnipresent in all industries. What Is Unsupervised Machine Learning? If you’ve ever come across deep learning, you might have heard about two methods to teach machines: supervised and unsupervised. Source ].

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Data Science Journey Walkthrough – From Beginner to Expert

Smart Data Collective

Here are the chronological steps for the data science journey. First of all, it is important to understand what data science is and is not. Data science should not be used synonymously with data mining. Mathematics, statistics, and programming are pillars of data science. Deep Learning.

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Choosing the right Machine Learning Framework

Domino Data Lab

Companies can choose to build their own custom machine learning framework, but most organizations choose an existing framework that fits their needs. In this article, we’ll show key considerations for selecting the right machine learning framework for your project and briefly review four popular ML frameworks.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

The fields have evolved such that to work as a data analyst who views, manages and accesses data, you need to know Structured Query Language (SQL) as well as math, statistics, data visualization (to present the results to stakeholders) and data mining. Machine learning and deep learning are both subsets of AI.