Github

JANUARY 24, 2019

In our 2018 Octoverse report, we noticed machine learning and data science were popular topics on GitHub. We decided to dig a little deeper into the state of machine learning and data science on GitHub. Julia, R, and Scala all appear in the top 10 for machine learning projects but not for GitHub overall.

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O'Reilly Media - Ideas

FEBRUARY 4, 2019

In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. You can find full results from the survey in the free report “Evolving Data Infrastructure”.). Data Platforms.

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CTOvision

OCTOBER 25, 2016

One possible solution, as you might have guessed, is machine learning. Machine learning algorithms, trained on the characteristics of particular networks, are likely to be far more successful at identifying real threats and notifying the right people. It was originally an Intel project called Open Network Insight (ONI).

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Artificial Inteligence Machine Learning Enterprise Open Source 114

TechCrunch

APRIL 11, 2023

When DBeaver creator Serge Rider began building an open source database admin tool in 2013, he probably had no idea that 10 years later, it would boast more than 8 million users. CEO Tatiana Krupenya says that it’s an administrative tool that allows anyone to access data from a variety of sources.

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CIO

APRIL 22, 2022

What is data science? Data science is a method for gleaning insights from structured and unstructured data using approaches ranging from statistical analysis to machine learning. For more details on data science bootcamps, see “ 15 best data science bootcamps for boosting your career.”.

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Data Artificial Inteligence Machine Learning Analytics 210

Invid Group

MARCH 19, 2024

What Is Machine Learning Used For? By INVID With the rise of AI, the term “machine learning” has grown increasingly common in today’s digitally driven world, where it is frequently credited with being the impetus behind many technical breakthroughs. Let’s break it down. Take retail, for instance.

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CIO

DECEMBER 11, 2024

It was not alive because the business knowledge required to turn data into value was confined to individuals minds, Excel sheets or lost in analog signals. We are now deciphering rules from patterns in data, embedding business knowledge into ML models, and soon, AI agents will leverage this data to make decisions on behalf of companies.

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O'Reilly Media - Ideas

MAY 21, 2019

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in London earlier this year. Use ML to unlock new data types—e.g.,

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CTOvision

OCTOBER 18, 2013

Eminent network scientist Laszlo Barabasi recently penned an op-ed calling on fellow scientists to spearhead the ethical use of big data. Frustrated Harvard Business Review blogger Andrew McAfee recently called on pundits to “stop sounding ignorant about big data.”

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Big Data Data Technical Review Government 103

CIO

JANUARY 19, 2024

Whether you’re looking to earn a certification from an accredited university, gain experience as a new grad, hone vendor-specific skills, or demonstrate your knowledge of data analytics, the following certifications (presented in alphabetical order) will work for you. Check out our list of top big data and data analytics certifications.)

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O'Reilly Media - Ideas

FEBRUARY 11, 2019

Highlights and use cases from companies that are building the technologies needed to sustain their use of analytics and machine learning. In a forthcoming survey, “Evolving Data Infrastructure,” we found strong interest in machine learning (ML) among respondents across geographic regions. Deep Learning.

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Big Data Technology Tools Cloud 108

CTOvision

DECEMBER 21, 2013

By Bob Gourley If you are an analyst or executive or architect engaged in the analysis of big data, this is a “must attend” event. Registration is now open for the third annual Federal Big Data Apache Hadoop Forum! 6, as leaders from government and industry convene to share Big Data best practices.

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O'Reilly Media - Ideas

JUNE 26, 2019

To successfully integrate AI and machine learning technologies, companies need to take a more holistic approach toward training their workforce. Implementing and incorporating AI and machine learning technologies will require retraining across an organization, not just technical teams.

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Artificial Inteligence Machine Learning Organization Training 107

Confluent

FEBRUARY 6, 2019

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. Impedance mismatch between data scientists, data engineers and production engineers.

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TechCrunch

SEPTEMBER 7, 2021

Talis Capital and Speedinvest co-led this round, with participation also from previous backer BoxOne Ventures and a grant from the Chan Zuckerberg Initiative, Mark Zuckerberg and Dr. Priscilla Chan’s effort to back open source software projects for science applications.

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TechCrunch

SEPTEMBER 29, 2021

There are increasing numbers of FaaS (farming as a service) startups that are looking to help farmers manage crop yields and plug into IoT sensors or data such as weather platforms. million and Ekylibre (France) is an open source ERP for farmers which has raised an undisclosed Series A.

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Hacker Earth Developers Blog

JANUARY 22, 2020

Right from programming projects such as data mining and Machine Learning, Python is the most favored programming language. Some of the common job roles requiring Python as a skill are: Data scientists . Data analyst. Machine Learning engineer. Machine Learning developers. Tech leads.

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CIO

JUNE 7, 2022

Predictive analytics applies techniques such as statistical modeling, forecasting, and machine learning to the output of descriptive and diagnostic analytics to make predictions about future outcomes. In business, predictive analytics uses machine learning, business rules, and algorithms.

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Analytics Data Analysis Business Analytics 203

Linux Academy

APRIL 10, 2019

He then covered the new focus on cloud security with an emphasis on access log transparency, data loss prevention, and VPC service controls such as Policy Intelligence, a machine learning-based service that targets access that may be too broad. Cloud Data Fusion. Big data got some big news today as well.

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Openxcell

MARCH 23, 2023

But with technological progress, machines also evolved their competency to learn from experiences. This buzz about Artificial Intelligence and Machine Learning must have amused an average person. But knowingly or unknowingly, directly or indirectly, we are using Machine Learning in our real lives.

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Artificial Inteligence Machine Learning Examples Artificial Intelligence 98

DataRobot

OCTOBER 18, 2022

Organizations are looking for AI platforms that drive efficiency, scalability, and best practices, trends that were very clear at Big Data & AI Toronto. DataRobot Booth at Big Data & AI Toronto 2022. Today, his team is using open-source packages without a standardized AI platform.

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d2iq

FEBRUARY 19, 2021

Going from a prototype to production is perilous when it comes to machine learning: most initiatives fail , and for the few models that are ever deployed, it takes many months to do so. As little as 5% of the code of production machine learning systems is the model itself. Adapted from Sculley et al.

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CTOvision

JUNE 3, 2014

SAN JOSE, Calif. , June 3, 2014 /PRNewswire/ – Hadoop Summit – According to the O’Reilly Data Scientist Salary Survey , R is the most-used tool for data scientists, while Weka is a widely used and popular open source collection of machine learning algorithms. Product Availability.

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TechCrunch

JULY 6, 2022

IBM today announced that it acquired Databand , a startup developing an observability platform for data and machine learning pipelines. Databand employees will join IBM’s data and AI division, with the purchase expected to close on June 27. million prior to the acquisition.

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Altexsoft

MAY 27, 2020

Machine learning (ML) history can be traced back to the 1950s, when the first neural networks and ML algorithms appeared. Analysis of more than 16.000 papers on data science by MIT technologies shows the exponential growth of machine learning during the last 20 years pumped by big data and deep learning advancements.

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Cloudera

JANUARY 20, 2021

Machine learning is now being used to solve many real-time problems. One big use case is with sensor data. Corporations now use this type of data to notify consumers and employees in real-time. With this example as inspiration, I decided to build off of sensor data and serve results from a model in real-time.

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Cloudera

OCTOBER 3, 2022

You’ve found an awesome data set that you think will allow you to train a machine learning (ML) model that will accomplish the project goals; the only problem is the data is too big to fit in the compute environment that you’re using. <end code block> Launching workers in Cloudera Machine Learning.

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CTOvision

JUNE 15, 2015

You know Spark, the free and open source complement to Apache Hadoop that gives enterprises better ability to field fast, unified applications that combine multiple workloads, including streaming over all your data. They also launched a plan to train over a million data scientists and data engineers on Spark.

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O'Reilly Media - Data

MAY 3, 2018

There are already systems for doing BI on sensitive data using hardware enclaves , and there are some initial systems that let you query or work with encrypted data (a friend recently showed me HElib , an open source, fast implementation of homomorphic encryption ). Machine learning. Closing thoughts.

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Analytics Artificial Inteligence Data Machine Learning 186

Altexsoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Which Big Data tasks does Spark solve most effectively? How does it work?

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Big Data Tools Data Storage 98

CTOvision

FEBRUARY 20, 2015

Azure Machine Learning Aims to Convert Data to Information (technewsworld.com). Qubole adds Apache Spark to its Big Data-as-a-Service platform (sdtimes.com). An Open Microsoft: Azure HDInsight Available for Linux (windowsitpro.com). IBM makes big data push (channeleye.co.uk).

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Google Cloud Cloud Big Data Azure 108

Cloudera

NOVEMBER 19, 2020

In financial services, another highly regulated, data-intensive industry, some 80 percent of industry experts say artificial intelligence is helping to reduce fraud. Machine learning algorithms enable fraud detection systems to distinguish between legitimate and fraudulent behaviors.

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Altexsoft

MAY 14, 2021

Big Data enjoys the hype around it and for a reason. But the understanding of the essence of Big Data and ways to analyze it is still blurred. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics. Key Big Data characteristics.

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TechCrunch

JANUARY 12, 2021

Winterstein notes that its efforts were all open source-based and that the company was “not commercial at all, a lot of tech geeks and German engineering types that were not overly experienced in go-to-market strategies.” In any case, there are no plans for an exit anytime soon with growth going strong.

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CIO

MAY 16, 2024

These planning tools are constantly transforming at the cutting edge using high performance computing, big data capabilities, and sophisticated intelligence,” Prouty notes. At UPS, Parameswaran gained experience developing machine learning models and generative AI applications and plans to exploit that at Baldor when possible.

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TechCrunch

JUNE 30, 2022

. “[We] launched Snowplow to help any company create granular behavioral data for themselves, in their own cloud — freeing data analysts and scientists from the constraints imposed by analytics vendors.” That figure spans organizations using Snowplow’s open source platform as well as its fully managed product.)

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Data Analytics Business Intelligence Google Cloud 187

CIO

JANUARY 20, 2023

Here’s what to consider: Ingesting the data : To be able to analyze more data at greater speeds, organizations need faster processing via high-powered servers and the right chips for AI—whether CPUs or GPUs. Protecting the data : Cyber threats are everywhere—at the edge, on-premises and across cloud providers.

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