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How to take machine learning from exploration to implementation

O'Reilly Media - Data

Interest in machine learning (ML) has been growing steadily , and many companies and organizations are aware of the potential impact these tools and technologies can have on their underlying operations and processes. Machine Learning in the enterprise". Scalable Machine Learning for Data Cleaning.

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Core technologies and tools for AI, big data, and cloud computing

O'Reilly Media - Ideas

Highlights and use cases from companies that are building the technologies needed to sustain their use of analytics and machine learning. This concurs with survey results we plan to release over the next few months. I’ll also highlight some interesting uses cases and applications of data, analytics, and machine learning.

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Analyst One Announces Top Analytical Technologies List

CTOvision

H2O is the open source math & machine learning platform for speed and scale. Alpine has simplified popular machine-learning methods and made them available on petabyte-scale datasets. We list our methodologies at the end of the list. The Analyst One Top Technologies List. and New York.

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The state of data quality in 2020

O'Reilly Media - Ideas

Those suspicions were confirmed when we quickly received more than 1,900 responses to our mid-November survey request. Key survey results: The C-suite is engaged with data quality. CxOs, vice presidents, and directors account for 20% of all survey respondents. Roles of survey respondents. Industries of survey respondents.

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Structural Evolutions in Data

O'Reilly Media - Ideas

And then there was the other problem: for all the fanfare, Hadoop was really large-scale business intelligence (BI). They’d grown tired of learning what is; now they wanted to know what’s next. Stage 2: Machine learning models Hadoop could kind of do ML, thanks to third-party tools.

Data 102
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The Good and the Bad of Apache Spark Big Data Processing

Altexsoft

Maintained by the Apache Software Foundation, Apache Spark is an open-source, unified engine designed for large-scale data analytics. Its flexibility allows it to operate on single-node machines and large clusters, serving as a multi-language platform for executing data engineering , data science , and machine learning tasks.

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The Good and the Bad of Docker Containers

Altexsoft

Docker is an open-source containerization software platform: It is used to create, deploy and manage applications in virtualized containers. Launched in 2013 as an open-source project, the Docker technology made use of existing computing concepts around containers, specifically the Linux kernel with its features.