Remove Deep Learning Remove Hadoop Remove Support Vector Machines
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Big Data Syllabus: A Comprehensive Overview

Pickl AI

Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers. It is built on the Hadoop Distributed File System (HDFS) and utilises MapReduce for data processing. Once data is collected, it needs to be stored efficiently.

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

IBM Journey to AI blog

Today, machine learning has evolved to the point that engineers need to know applied mathematics, computer programming, statistical methods, probability concepts, data structure and other computer science fundamentals, and big data tools such as Hadoop and Hive. Machine learning and deep learning are both subsets of AI.

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Must-Have Skills for a Machine Learning Engineer

Pickl AI

Without linear algebra, understanding the mechanics of Deep Learning and optimisation would be nearly impossible. Support Vector Machines (SVM) SVMs are powerful classifiers that separate data into distinct categories by finding an optimal hyperplane. Neural networks are the foundation of Deep Learning techniques.

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What Does the Modern Data Scientist Look Like? Insights from 30,000 Job Descriptions

ODSC - Open Data Science

Machine Learning As machine learning is one of the most notable disciplines under data science, most employers are looking to build a team to work on ML fundamentals like algorithms, automation, and so on. Deep Learning Deep learning is a cornerstone of modern AI, and its applications are expanding rapidly.