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Best of arXiv.org for AI, Machine Learning, and Deep Learning – October 2018

In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.

The Math Behind Machine Learning

What math subjects are used in machine learning, and how are they used? In this research paper by Richard Han, Ph.D., we look at the mathematics behind the machine learning techniques linear regression, linear discriminant analysis, logistic regression, artificial neural networks, and support vector machines.

The Math Behind Machine Learning

Machine learning is a wildly popular field of technology that is being used by data scientists around the globe. Mastering machine learning can be achieved via many avenues of study, but one arguably necessary ingredient to success is a fundamental understanding of the mathematics behind the algorithms. Some data scientists-in-training often try to take a […]

Why Big Data and Machine Learning are Essential for Cyber Security

In this contributed article, Shachar Shamir, COO of Ranky, suggests that big data and machine learning are essential for cyber security. Using machine learning to automate attack detection and response, companies can have a quick and robust cyber defense system, one where security professionals work side-by-side sophisticated automated tools.

Introduction to Statistical Analysis and Outlier Detection Methods

Our friends over at Noah Data have written a research style paper, “Introduction to Statistical Analysis and Outlier Detection Methods,” that discusses how statistical data can generally be classified in terms of number of variables as Univariate, Bivariate or Multivariate. Univariate data has only one variable, Bivariate data has two variables and Multivariate data has more than two variables.

New Update for Oracle Autonomous Database to Secure Data and Accelerate Innovation

Today Oracle previewed significant new capabilities and deployment options for Oracle Autonomous Database. The new features illustrate Oracle’s continuing commitment to its global cloud customers, who rely on the database to run their mission-critical systems.

Introduction to Statistical Analysis and Outlier Detection Methods

Our friends over at Noah Data have written a research style paper, Introduction to Statistical Analysis and Outlier Detection Methods, that discusses how statistical data can generally be classified in terms of number of variables as Univariate, Bivariate or Multivariate. Univariate data has only one variable, Bivariate data has two variables and Multivariate data has […]

Best of arXiv.org for AI, Machine Learning, and Deep Learning – September 2018

In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.

The insideBIGDATA IMPACT 50 List for Q4 2018

The team here at insideBIGDATA is deeply entrenched in following the big data ecosystem of companies from around the globe. We’re in close contact with most of the firms making waves in the technology areas of big data, data science, machine learning, AI and deep learning. Our in-box is filled each day with new announcements, commentaries, and insights about what’s driving the success of our industry so we’re in a unique position to publish our quarterly IMPACT 50 List of the most important movers and shakers in our industry. These companies have proven their relevance by the way they’re impacting the enterprise through leading edge products and services. We’re happy to publish this evolving list of the industry’s most impactful companies!

Databricks and RStudio Introduce New Version of MLflow with R Integration

Databricks, a leader in unified analytics and founded by the original creators of Apache Spark™, and RStudio, today announced a new release of MLflow, an open source multi-cloud framework for the machine learning lifecycle, now with R integration. RStudio has partnered with Databricks to develop an R API for MLflow v0.7.0.