O'Reilly Media - Ideas

JUNE 4, 2019

Proposals for the O’Reilly Open Source Software Conference emphasize cloud native, AI/ML, and data tools and topics. DevOps, cloud, big data, artificial intelligence (AI), and machine learning (ML)—is encoded in the record of speaker proposals from the O’Reilly Open Source Software Conference (OSCON).

Open Source 93

Open Source Artificial Inteligence Software Artificial Intelligence 93

Openxcell

JUNE 9, 2023

All this raw information, patterns and details is collectively called Big Data. Big Data analytics,on the other hand, refers to using this huge amount of data to make informed business decisions. Let us have a look at Big Data Analytics more in detail. What is Big Data Analytics?

Big Data 52

Big Data Analytics Tools Data 52

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.

Open Source 203

Open Source Database Administration Machine Learning Artificial Inteligence 203

InfoWorld

APRIL 11, 2024

The Apache Software Foundation develops and maintains open source software projects that significantly impact various domains of computing, from web servers and databases to big data and machine learning.

Analysis 79

Analysis Data IoT Machine Learning 79

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.

Machine Learning 111

Machine Learning Artificial Inteligence Software Review Systems Review 111

Hacker Earth Developers Blog

MAY 22, 2020

In our third episode of Breaking 404 , we caught up with Srivatsan Ramanujam, Director of Software Engineering: Machine Learning, Salesforce to discuss everything about Machine Learning and the best practices for ML engineers to excel in their careers. Again, focus on Data Science and Machine Learning.

Machine Learning 130

Machine Learning Artificial Inteligence Software Engineering Engineering 130

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.

Analytics 338

Analytics Data Analysis Business Analytics 338

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.

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Enterprise 111

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.

Artificial Inteligence 103

Artificial Inteligence Machine Learning Technical Review Software Review 103

O'Reilly Media - Data

AUGUST 16, 2018

The deployment of big data tools is being held back by the lack of standards in a number of growth areas. Technologies for streaming, storing, and querying big data have matured to the point where the computer industry can usefully establish standards. The main standard with some applicability to big data is ANSI SQL.

Big Data 124

Big Data Data Storage Azure 124

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.

Machine Learning 89

Machine Learning Artificial Inteligence Architecture Training 89

Dzone - DevOps

MARCH 20, 2024

In the age of Big Data and Artificial Intelligence (AI), effectively managing and deploying machine learning (ML) models is essential for businesses aiming to leverage data-driven insights.

Artificial Inteligence 71

Artificial Inteligence Artificial Intelligence Machine Learning Open Source 71

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.

Google Cloud 97

Google Cloud Big Data Cloud Data 97

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.

Machine Learning 107

Machine Learning Artificial Inteligence Scalability Data Engineering 107

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).

Artificial Inteligence 114

Artificial Inteligence Machine Learning Enterprise Open Source 114

The Crazy Programmer

MARCH 15, 2021

It is frequently used in developing web applications, data science, machine learning, quality assurance, cyber security and devops. Python emphasizes on code readability and therefore has simple and easy to learn syntax. Python is often employed in developing machine language and deep learning applications.

Programming 317

Programming Open Source Quality Assurance Trends 317

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.

Big Data 86

Big Data Technology Tools Cloud 86

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.

Sustainability 205

Sustainability Machine Learning Artificial Inteligence IoT 205

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.

Machine Learning 111

Machine Learning Artificial Inteligence Applications Data 111

CIO

JULY 14, 2023

A general LLM won’t be calibrated for that, but you can recalibrate it—a process known as fine-tuning—to your own data. Fine-tuning applies to both hosted cloud LLMs and open source LLM models you run yourself, so this level of ‘shaping’ doesn’t commit you to one approach.

Generative AI 246

Generative AI Artificial Inteligence Open Source ChatGPT 246

CIO

JUNE 7, 2023

These leaders succeed with these real-time AI capabilities in large part because of their ability to aggregate massive amounts of real-time data from customers, devices, sensors, or partners as it moves through applications. This data in turn is used to train and serve machine learning models.

Organization 130

Organization Artificial Inteligence Open Source Architecture 130

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.

Technical Review 216

Technical Review Machine Learning Artificial Inteligence Software Review 216

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.

Big Data 113

Big Data CTO Data Government 113

CTOvision

JULY 9, 2014

The term “Big Data” has become synonymous with this evolution. But still, many of our customers continue to ask, “What is Big Data?”, “What are its use cases?”, What is Big Data? The data is too big, moves too fast, or does not fit the structures of your database architectures.

Big Data 114

Big Data Data CTO Fractional CTO 114

AWS Machine Learning - AI

DECEMBER 12, 2023

In this post, we’ll summarize training procedure of GPT NeoX on AWS Trainium , a purpose-built machine learning (ML) accelerator optimized for deep learning training. His research interests include foundational models, reinforcement learning, and asynchronous optimization. We’ll outline how we cost-effectively (3.2

AWS 93

AWS Artificial Inteligence Training Meeting 93

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.

Machine Learning 113

Machine Learning Artificial Inteligence Big Data Data 113

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.

Software Review 170

Software Review Artificial Inteligence Technical Review Analytics 170

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.

Open Source 117

Open Source Big Data Machine Learning Artificial Inteligence 117

Cloudera

AUGUST 3, 2021

Advanced analytics and enterprise data empower companies to not only have a completely transparent view of movement of materials and products within their line of sight, but also leverage data from their suppliers to have a holistic view 2-3 tiers deep in the supply chain. Open source solutions reduce risk.

Analytics 107

Analytics Open Source Government Machine Learning 107

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).

Google Cloud 108

Google Cloud Cloud Big Data Azure 108

CTOvision

FEBRUARY 7, 2014

By Bob Gourley H2O brings better algorithms to big data. H2O is a fast open source in-memory prediction engine and machine learning platform. With H2O enterprises can use all of their data (instead of sampling) in real-time for better predictions. For more see: [link]. Related articles.

Analytics 66

Analytics Machine Learning Artificial Inteligence Big Data 66

Cloudera

FEBRUARY 7, 2019

Enabling this transformation is the HDP platform, along with SAS Viya on Google Cloud , which has delivered machine learning models and personalization at scale. Hortonworks has a strong support model and commitment to open source for large organizations, enabling it to be the chosen provider of service for ATB.

Big Data 63

Big Data Analytics Google Cloud Cloud 63

AWS Machine Learning - AI

JANUARY 26, 2024

The goal of this post is to empower AI and machine learning (ML) engineers, data scientists, solutions architects, security teams, and other stakeholders to have a common mental model and framework to apply security best practices, allowing AI/ML teams to move fast without trading off security for speed.

Artificial Inteligence 118

Artificial Inteligence Generative AI Security Applications 118

CTOvision

FEBRUARY 1, 2017

30, 2017 /PRNewswire/ -- DataRobot , an industry leader in machine learning (ML) and artificial intelligence (AI), today announced it is expanding into the federal market, beginning with the appointment of a Vice President of Public Sector. The press release below gives us reason to hold them in even higher regard: BOSTON , Jan.

Artificial Inteligence 97

Artificial Inteligence Artificial Intelligence Marketing Machine Learning 97

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. The cloud native table format was open sourced into Apache Iceberg by its creators.

Data 89

Data Analytics Open Source Architecture 89

Perficient

FEBRUARY 13, 2024

Databricks is a cloud-based data processing and data warehousing platform that has gained immense popularity in recent years. It was developed by the creators of Apache Spark, an open-source big data processing framework. to automate the generation of test cases for their data pipelines.

Artificial Inteligence 52

Artificial Inteligence Analytics Machine Learning Testing 52

Hu's Place - HitachiVantara

MAY 10, 2019

Rule-based fraud detection software is being replaced or augmented by machine-learning algorithms that do a better job of recognizing fraud patterns that can be correlated across several data sources. The machine learning models need to be trained using historic data.

Data 90

Data Machine Learning Artificial Inteligence Weak Development Team 90