AI & Machine Learning

The Top 5 Data Trends for CDOs to Watch Out for in 2021

What will 2021 bring to the data world? How will data infrastructure evolve to keep up with all the latest innovations and changes? This year, we’ll see several new data trends.

Implement Expectation-Maximization Algorithm(EM) in Python from Scratch

This article explores how to train Gaussian Mixture Models with the Expectation-Maximization Algorithm and implemente it in Python to solve unsupervised and semi-supervised learning problems.

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Modelling and Simulations in Data Science

One of the main limitations of the current state of Machine Learning and Deep Learning, is the constant need for new data.

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  • The Evolution of Enterprise Knowledge Graphs and the CNS

    This blog will speculate on how enterprise knowledge graphs (EKGs) will evolve to contain specialized functions and specialized subgraphs.

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    Top Applications of Graph Neural Networks 2021

    Graphs emerge in the context of users’ interactions with products in e-commerce platforms and as a result, there are many companies that employ GNNs for product recommendation.

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    Wearable AI- Implementation and Benefits in Digital World

    AI technology powered wearable devices are continually making pathways to make a foray across untapped industries like telecommunication, finance, etc. The digital cosmos is pushing its boundaries every day to amplify user experience for a better living.

    6 MINUTES READ Continue Reading »

    Succeed in the Intelligent Era with an End-to-End Data Management Framework

    Enterprises drowning in the implications of data need an end-to-end management platform. Managing data on several public and private clouds can be too much to handle. Know what a good end-to-end data management system should include.

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    Ensemble Learning: Bagging & Boosting

    Learn how to combine weak learners to build a stronger learner to reduce bias and variance in your ML model

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    What Is Semi-Supervised Machine Learning?

    Semi-supervised learning is a brilliant technique that can come handy if you know when to use it. You can use semi-supervised learning, a machine learning technique that can automate the data-labeling process with a bit of help.

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    AI-Enabled Monitoring Can Help Solve Data Storage Issues

    AI data storage systems can recognize patterns in arrays and stacks to predict storage issues and help solve them.

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    How To Become a Data Engineer

    Data engineer is a team player who is working with data analysts, scientists, infrastructure engineers and other stakeholders. So do not forget about soft skills like empathy, understanding a business domain, open-mindedness etc.

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    We Don’t Need Data Scientists, We Need Data Engineers

    There are 70% more open roles at companies in data engineering as compared to data science. As we train the next generation of data and machine learning practitioners, let’s place more emphasis on engineering skills.

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