Remove Artificial Intelligence Remove Data Engineering Remove Hadoop
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How Rocket Companies modernized their data science solution on AWS

AWS Machine Learning Blog

Rockets legacy data science environment challenges Rockets previous data science solution was built around Apache Spark and combined the use of a legacy version of the Hadoop environment and vendor-provided Data Science Experience development tools. This also led to a backlog of data that needed to be ingested.

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Big Data Skill sets that Software Developers will Need in 2020

Smart Data Collective

Whether they want a career as an app developer or data analyst, the skillsets below can help them find lucrative careers in a competitive job market. Big Data Skillsets. From artificial intelligence and machine learning to blockchains and data analytics, big data is everywhere. NoSQL and SQL.

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Big Data – Das Versprechen wurde eingelöst

Data Science Blog

Big Data tauchte als Buzzword meiner Recherche nach erstmals um das Jahr 2011 relevant in den Medien auf. Big Data wurde zum Business-Sprech der darauffolgenden Jahre. In der Parallelwelt der ITler wurde das Tool und Ökosystem Apache Hadoop quasi mit Big Data beinahe synonym gesetzt. Artificial Intelligence (AI) ersetzt.

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The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering

Pickl AI

Unfolding the difference between data engineer, data scientist, and data analyst. Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

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Retrieval-Augmented Generation with LangChain, Amazon SageMaker JumpStart, and MongoDB Atlas semantic search

Flipboard

MongoDB vector data store MongoDB Atlas Vector Search is a new feature that allows you to store and search vector data in MongoDB. Vector data is a type of data that represents a point in a high-dimensional space. This type of data is often used in ML and artificial intelligence applications.

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Business Analytics vs Data Science: Which One Is Right for You?

Pickl AI

Programming languages like Python and R are commonly used for data manipulation, visualization, and statistical modeling. Machine learning algorithms play a central role in building predictive models and enabling systems to learn from data. Big data platforms such as Apache Hadoop and Spark help handle massive datasets efficiently.

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A Guide to Choose the Best Data Science Bootcamp

Data Science Dojo

Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. Data Processing and Analysis : Techniques for data cleaning, manipulation, and analysis using libraries such as Pandas and Numpy in Python.