Dataiku

APRIL 19, 2023

One of the most fundamental concepts to master when getting up to speed with machine learning basics is supervised vs. unsupervised machine learning. This blog post provides a brief rundown, visuals, and a few examples of supervised and unsupervised machine learning to take your ML knowledge to the next level.

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Dataiku

JUNE 21, 2021

While some automation in machine learning (ML) models is productive and necessary, taking a human-centric approach to machine learning and AI is essential. Humans have to be part of the ML workflow, included in the feedback loop, and more.

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Cloudera

NOVEMBER 1, 2023

Embrace the new capabilities Our new LLM chatbot AMP, enhanced by Pinecone’s vector database and real-time embedding ingestion, is a testament to our dedication to pushing the boundaries in applied machine learning. We invite you to explore the improved functionalities of this latest AMP.

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Cloudera

FEBRUARY 11, 2022

Advances in the development and application of Machine Learning (ML) and Deep Learning (DL) algorithms, require greater care to ensure that the ethics embedded in previous rule-based systems are not lost. This blog post hopes to provide this foundational understanding. What is Machine Learning.

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Confluent

DECEMBER 11, 2020

This blog post shows how transactional machine learning (TML) integrates data streams with automated machine learning (AutoML), using Apache Kafka® as the data backbone, to create a frictionless machine learning […].

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Coding Dojo

JULY 18, 2022

When people hear about deep learning and machine learning, many assume they’re the same. The post Deep Learning vs. Machine Learning: What’s the Difference? appeared first on Coding Dojo Blog. Although both belong to the artificial … Read more >>.

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Dataiku

FEBRUARY 2, 2024

Quantum Machine Learning (QML) leverages quantum computing to solve challenging ML problems that classical computers cannot efficiently handle.

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Xebia

MARCH 17, 2021

The post Burst your bubble: using machine learning to change the world appeared first on Xebia Blog. How to improve the world with technology.

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DevOps.com

JULY 7, 2020

Amazon Web Services (AWS) has made generally available a tool dubbed Amazon CodeGuru that employs machine learning algorithms to recommend ways to improve code quality and identify which lines of code are the most expensive to run on its cloud service.

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DevOps.com

MAY 20, 2021

The post Three Ways Machine Learning Can Change Incident Management appeared first on DevOps.com. Typically, there is a critical problem, ranging from complete failure to loss of certain functionality or performance. The problem or outage potentially means loss of revenue, loss of customers, […].

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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.

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Netflix Tech

MARCH 4, 2024

In this blog post, we present our project on Auto Remediation, which integrates the currently used rule-based classifier with an ML service and aims to automatically remediate failed jobs without human intervention. Right Sizing is in progress and will be covered with more details in a dedicated technical blog post later. Stay tuned.

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DevOps.com

FEBRUARY 6, 2024

OpenText updated a static analysis code auditing tool using machine learning algorithms to provide deeper insights into on-premises IT environments.

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Openxcell

MARCH 21, 2023

MACHINE LEARNING- the most hyped technology these days due to its ability to automate tasks, detect patterns and learn from the data. In this blog, you will find out the importance of Machine Learning and how it is changing the environment around us. What is Machine Learning?

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Cloudera

APRIL 9, 2021

This is part 4 in this blog series. This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The second blog dealt with creating and managing Data Enrichment pipelines. Here are the key stages: .

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DevOps.com

JANUARY 4, 2021

The company says its Purchase Planner tool uses machine learning to optimize cloud computing workloads by automatically purchasing cloud reserve instances based on the forecasts it generates. Purchase Planner leverages the machine learning algorithms […]. The post Reserved.ai

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O'Reilly Media - Ideas

JUNE 9, 2020

The biggest problem facing machine learning today isn’t the need for better algorithms; it isn’t the need for more computing power to train models; it isn’t even the need for more skilled practitioners. It’s getting machine learning from the researcher’s laptop to production.

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Dataiku

NOVEMBER 8, 2023

The gap between research in the machine learning (ML) space and how people actually leverage ML in an enterprise context can be wide. Case in point: large language models (LLMs) and Generative AI. That’s why the Dataiku AI Lab seeks to build a bridge between ML research and practical business applications.

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Palo Alto Networks

JUNE 1, 2023

ChatGPT, a language-based machine learning model, is not exempt from this discussion. The post Cracking the Code — How Machine Learning Supercharges Threat Detection appeared first on Palo Alto Networks Blog. While ChatGPT presents promising opportunities in cybersecurity, it also raises ethical considerations.

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Hacker Earth Developers Blog

DECEMBER 26, 2018

According to the Global Banking Outlook 2018 study conducted by Ernst & Young, 60-80% of the banks are planning to increase investment in data and analytics and 40-60% plan to increase investment in machine learning. Analytics and machine learning on their own are mere buzzwords. Impact areas.

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DevOps.com

MAY 21, 2020

The post A Buyer’s Guide to AI and Machine Learning appeared first on DevOps.com. But, when we say “AI is doing this,” our buyers often know so little about AI that they don’t ask the hard questions. In industries like the DevTools space, it is crucial […].

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Dataiku

NOVEMBER 11, 2020

The next step in our fairness journey is to dig into how to detect biased machine learning models. In our previous article , we gave an in-depth review on how to explain biases in data.

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Mentormate

DECEMBER 12, 2023

In a previous blog post, we introduced a five-phase framework to plan out Artificial Intelligence (AI) and Machine Learning (ML) initiatives. The Traditional Machine Learning Workflow Initiating a traditional ML project begins with collecting data. How does this help us in practice?

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Dataiku

MARCH 30, 2023

This blog post was created in collaboration with Andrea Castellani , Ph.D. researcher at Bielefeld University in the Machine Learning research group. Among his research topics, he has significant experience in using digital twins for anomaly detection.

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Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. We will learn what it is, why it is important and how Cloudera Machine Learning (CML) is helping organisations tackle this challenge as part of the broader objective of achieving Ethical AI.

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DataRobot

DECEMBER 6, 2022

Savvy data scientists are already applying artificial intelligence and machine learning to accelerate the scope and scale of data-driven decisions in strategic organizations. Explore these 10 popular blogs that help data scientists drive better data decisions. Read the blog. Read the blog. Read the blog.

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DevOps.com

JUNE 2, 2020

The use of artificial intelligence (AI) and machine learning (ML) is fundamentally changing the way we think about DevOps. The post How DevOps Powered by AI and Machine Learning Is Delivering Business Transformation appeared first on DevOps.com. For many, this will be the crucial next […].

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DevOps.com

NOVEMBER 7, 2019

As organizations add machine learning (ML) to their workflows, it’s tempting to try to squeeze model creation and deployment into the existing software development lifecycle (SDLC). The post Five Challenges of Machine Learning DevOps appeared first on DevOps.com. We have identified […].

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CIO

MAY 2, 2024

According to a recent Microsoft blog , organizations can use security and compliance solutions in Microsoft 365 E5 to have visibility into their threat landscape and leverage built-in AI and machine learning in Microsoft Sentinel and Microsoft Defender for Cloud to proactively manage threats and reduce alert fatigue.

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Lacework

APRIL 19, 2022

Machine Learning (ML) is absolutely everywhere. The big three cloud service providers—AWS, Azure, and Google Cloud—have a ton of different machine learning services, with more on the way. Success stories around machine learning hint at unique and novel solutions to really challenging problems.

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DevOps.com

DECEMBER 19, 2023

Here are six distinct technology trends that are poised to be particularly influential for DevOps and software development in the new year.

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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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Cloudera

NOVEMBER 19, 2021

We are excited by the endless possibilities of machine learning (ML). We recognise that experimentation is an important component of any enterprise machine learning practice. Continuous Operations for Production Machine Learning (COPML) helps companies think about the entire life cycle of an ML model.

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Dataiku

APRIL 8, 2020

How can the game of checkers be used to illustrate specific machine learning functions? Find out the answers in this blog post. What role does the human play in the process?

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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. Therefore, the majority of machine learning/deep learning frameworks focus on Python APIs.

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Datavail

MARCH 8, 2022

were unsuccessful in fulfilling their aspirations of implementing Machine Learning (ML) systems in 2021. For more information regarding ML and selecting the right data models to get the most from it for your organization, download our white paper, “ Tips for Machine Learning Model Selection.”. Contact an Expert ».

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CIO

MAY 2, 2024

According to a recent Microsoft blog , organizations can use security and compliance solutions in Microsoft 365 E5 to have visibility into their threat landscape and leverage built-in AI and machine learning in Microsoft Sentinel and Microsoft Defender for Cloud to proactively manage threats and reduce alert fatigue.

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