Smart Data Collective

AUGUST 27, 2020

The plugin simplifies the process considerably without compromising system security. To learn more about the OpenShift plugin, go to the Integration Center bar at the bottom part of the Akeyless WebUI interface. The problem with this built-in feature of OpenShift, however, is that the secrets are only encoded, not encrypted.

Clustering 87

Clustering Database Azure AWS 87

Dataconomy

MARCH 19, 2024

Enhanced partnership between Google Cloud and NVIDIA is announced to support the machine learning (ML) community. Major Isaac platform updates include Isaac Lab for simulations and OSMO for data orchestration, facilitating robot learning.

Azure 113

Azure AWS AI AI 113

PyImageSearch

MARCH 30, 2023

If you want a gentle introduction to machine learning for computer vision, you’re in the right spot. Here at PyImageSearch we’ve been helping people just like you master deep learning for computer vision. Also, you might want to check out our computer vision for deep learning program before you go.

Machine Learning 56

Machine Learning Machine Learning Deep Learning Deep Learning 56

Towards AI

MARCH 20, 2023

What is the role of unsupervised learning in generative AI? How can we ensure the security and privacy of generative AI models? Can generative AI models be used for reinforcement learning? Traditional AI models, such as classification or regression algorithms, solve specific problems by finding correlations in the data.

Natural Language Processing 69

Natural Language Processing AI AI Algorithm 69

Cambridge Intelligence

JANUARY 30, 2023

Supply chain managers have plenty of tools to work with, from smart IoT sensor technology to machine learning and real-time data analytics. Healthcare & pharmaceuticals Every organization needs a fast, reliable and secure supply chain. We need to trace its movements through the supply chain to find out the scale of the problem.

Analytics 86

Analytics Analytics Data Visualization Machine Learning 86

O'Reilly Media

MARCH 12, 2024

It’s important to make sure that you can capture enough relevant data to predict problems before they become problems; only capturing enough data for a post-mortem analysis isn’t sufficient. AI introduces many new problems that developers and IT staff will need to deal with. That code is frequently insecure.

AI 16

AI AI Algorithm Database 16

Cambridge Intelligence

FEBRUARY 27, 2023

40,000 nodes and links visualized using KeyLines Does it tick the right boxes for your C-suite executives? We see this in security and intelligence, fraud detection and cybersecurity markets, but the same is true in many other popular use cases. You want your competitors to wish they’d chosen your option too.

Data Visualization 52

Data Visualization Algorithm Analytics Analytics 52

AWS Machine Learning Blog

APRIL 5, 2023

Amazon SageMaker Serverless Inference is a purpose-built inference service that makes it easy to deploy and scale machine learning (ML) models. In this phase, you submit a text search query or image search query through the deep learning model (CLIP) to encode as embeddings. You can use CLIP with Amazon SageMaker to perform encoding.

AWS 87

AWS ML ML K-nearest Neighbors 87

AWS Machine Learning Blog

APRIL 29, 2024

For AWS and Outerbounds customers, the goal is to build a differentiated machine learning and artificial intelligence (ML/AI) system and reliably improve it over time. This often means the method of using a third-party LLM API won’t do for security, control, and scale reasons.

AWS 99

AWS ML ML Python 99

Hacker News

FEBRUARY 8, 2024

Some years ago I did a talk at a local university on cybersecurity, titled “ Cyber and Information Security: Have We All Gone Mad? ” Software security is dire, which is a function both of the quality of the code and the sheer amount of it. The state of software security is dire. Yet we continue to rely on all these products.

Azure 181

Azure Cloud Computing AWS Python 181

AWS Machine Learning Blog

MARCH 15, 2024

In this post, we discuss the value and potential impact of federated learning in the healthcare field. Medical data restrictions You can use machine learning (ML) to assist doctors and researchers in diagnosis tasks, thereby speeding up the process. In the following sections, we discuss how federated learning can help.

AWS 98

AWS ML ML Data Silos 98

Data Science Dojo

JULY 24, 2023

Read more –> Big data problem, its impact, and a possible solution for it Introduction to big data engineering Big Data Engineering is the discipline that focuses on designing, building, and maintaining systems and solutions to process, store, and analyze massive datasets.

Big Data 195

Big Data Big Data Data Engineering Data Engineer 195

Ocean Protocol

AUGUST 23, 2023

In fact, Graunt was the first person to use data analysis to understand and solve a problem. With every innovation in technology, data science, machine learning , & artificial intelligence comes a new way of creating and spreading information, knowledge, or capital. Shorthand's answer is Blockchain technology.

Big Data 52

Big Data Big Data Algorithm Machine Learning 52

Data Science Dojo

JANUARY 12, 2023

Copious amounts of organized, semi-structured, and unstructured data can be stored, processed, and secured using a data lake, a centralized repository. Data is loaded into the Hadoop Distributed File System (HDFS) and stored on the many computer nodes of a Hadoop cluster in deployments based on the distributed processing architecture.

Data Lakes 221

Data Lakes Data Warehouse Hadoop Machine Learning 221

Cambridge Intelligence

DECEMBER 19, 2023

Data overload is a real problem for busy analysts. How do they spot the red flags in a cyber security network? This reduces their learning curve and helps them find value in their visualizations fast. When you overlay this information on a graph, your analysts see alerts in context and quickly discover where problems exist.

Data Visualization 59

Data Visualization Artificial Intelligence Artificial Intelligence Machine Learning 59

Dataconomy

MAY 22, 2023

Distributed learning has emerged as a crucial technique for tackling complex problems and harnessing the power of large-scale data processing. But what exactly is distributed learning in machine learning? Why is it so important? This process is often referred to as training or model optimization.

ML 233

ML ML Machine Learning Machine Learning 233

Pickl AI

JANUARY 15, 2023

Machine Learning and Artificial Intelligence have played the role of revolutionaries in the world of computing. Machine Learning is able to based on the data from the past predict patterns and trends of the future. This blog would act as a guide for you to understand the concept- What is Deep Learning?- How Deep Learning works?

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Smart Data Collective

FEBRUARY 14, 2023

We have talked about the impact that machine learning has had on website and app development. However, machine learning technology can also help solve Internet problems on a more granular level. Fortunately, machine learning technology shows some promise in addressing them. Finally, mesh networks are incredibly scalable.

Machine Learning 96

Machine Learning Machine Learning Supervised Learning Algorithm 96

AWS Machine Learning Blog

SEPTEMBER 18, 2023

Machine learning (ML) is becoming increasingly complex as customers try to solve more and more challenging problems. It’s a programming model that allows you to create distributed objects that maintain an internal state and can be accessed concurrently by multiple tasks running on different nodes in a Ray cluster.

Machine Learning 100

Machine Learning Machine Learning ML ML 100

Smart Data Collective

MAY 8, 2022

Blockchain databases are distributed, as well as transparent and secure. These users can also be considered as nodes. These nodes then work together with other nodes to ensure that changes are made to the database, when necessary. As a result, the process is made both transparent as well as secure. Conclusion.

Database 133

Database 133

AWS Machine Learning Blog

AUGUST 4, 2023

In Part 1 , we show how the Salesforce Data Cloud and Einstein Studio integration with SageMaker allows businesses to access their Salesforce data securely using SageMaker and use its tools to build, train, and deploy models to endpoints hosted on SageMaker. In the data flow view, you can now see a new node added to the visual graph.

ML 78

ML ML AWS AI 78

AWS Machine Learning Blog

OCTOBER 10, 2023

Machine learning (ML), especially deep learning, requires a large amount of data for improving model performance. Federated learning (FL) is a distributed ML approach that trains ML models on distributed datasets. Federated learning (FL) is a distributed ML approach that trains ML models on distributed datasets.

AWS 92

AWS ML ML Algorithm 92

IBM Journey to AI blog

JANUARY 18, 2023

They defined it as : “ A data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data. ”.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

Hacker News

SEPTEMBER 5, 2023

Since then, a steady trickle of six-figure cryptocurrency heists targeting security-conscious people throughout the tech industry has led some security experts to conclude that crooks likely have succeeded at cracking open some of the stolen LastPass vaults. “They truly all are reasonably secure. Then on Aug.

Computer Science 182

Computer Science Computer Science Analytics Analytics 182

AWS Machine Learning Blog

MAY 23, 2023

The seeds of a machine learning (ML) paradigm shift have existed for decades, but with the ready availability of virtually infinite compute capacity, a massive proliferation of data, and the rapid advancement of ML technologies, customers across industries are rapidly adopting and using ML technologies to transform their businesses.

AWS 91

AWS AI AI ML 91

Mlearning.ai

MARCH 9, 2023

Automated algorithms for image segmentation have been developed based on various techniques, including clustering, thresholding, and machine learning (Arbeláez et al., Understanding the robustness of image segmentation algorithms to adversarial attacks is critical for ensuring their reliability and security in practical applications.

Deep Learning 52

Deep Learning Deep Learning Algorithm Machine Learning 52

Google Research AI blog

FEBRUARY 10, 2023

We continued our efforts in developing new algorithms for handling large datasets in various areas, including unsupervised and semi-supervised learning , graph-based learning , clustering , and large-scale optimization. We provided a model-based taxonomy that unified many graph learning methods.

Algorithm 110

Algorithm Clustering ML ML 110

Smart Data Collective

SEPTEMBER 25, 2019

Foundations of Blockchain is for anyone who wants to dive into blockchain from first principles and learn how decentralized applications and cryptocurrencies really work. In a blockchain network, transactions are the main data that is exchanged between nodes. A few optimization techniques are described in the following sections.

Big Data 74

Big Data Big Data Business Intelligence Business Intelligence 74

Cambridge Intelligence

JANUARY 2, 2023

Fraud analysts and investigators face an expensive and complex problem: how do you keep up with the increasingly sophisticated strategies adopted by identity fraudsters at scale? Make sure it shares the same VPC as your Neptune instance and uses a new security group with correct permissions. valueMap(true).path().toList().then(data

Database 52

Database AWS Data Visualization Analytics 52

AWS Machine Learning Blog

JANUARY 13, 2023

To mitigate these challenges, we propose a federated learning (FL) framework, based on open-source FedML on AWS, which enables analyzing sensitive HCLS data. It involves training a global machine learning (ML) model from distributed health data held locally at different sites. Update your security groups to reference peer VPC groups.

AWS 70

AWS Analytics Analytics Machine Learning 70

AWS Machine Learning Blog

AUGUST 24, 2023

Today, we’re pleased to announce the preview of Amazon SageMaker Profiler , a capability of Amazon SageMaker that provides a detailed view into the AWS compute resources provisioned during training deep learning models on SageMaker. The following table provides the links to the supported AWS Deep Learning Containers for SageMaker.

AWS 77

AWS Deep Learning Deep Learning ML 77

AssemblyAI

NOVEMBER 9, 2023

The models are powered by advanced Deep Learning and Machine Learning research. In Natural Language Processing, or NLP, Text Summarization refers to the process of using Deep Learning and Machine Learning models to synthesize large bodies of texts into their most important parts. What is Text Summarization for NLP?

AI 102

AI AI Machine Learning Machine Learning 102

IBM Journey to AI blog

NOVEMBER 13, 2023

In broad strokes, the Kubernetes orchestration platform runs via containers with pods and nodes. Nodes run the pods and are usually grouped in a Kubernetes cluster, abstracting the underlying physical hardware resources. This mitigates potential issues like traffic surges, hardware problems or network disruptions.

Machine Learning 116

Machine Learning Machine Learning ML ML 116

Dataconomy

MAY 12, 2023

In the realm of distributed computing, the intricately orchestrated interplay of multiple interconnected nodes unfolds, akin to a meticulously choreographed symphony. Network:  The network establishes bridges between nodes within the distributed system, facilitating uninterrupted bidirectional flow of data and information.

Cloud Computing 87

Cloud Computing Clustering Database Data Analysis 87

AWS Machine Learning Blog

DECEMBER 4, 2023

An effective solution to this problem is the prediction of product categories. We capitalized on the powerful tools provided by AWS to tackle this challenge and effectively navigate the complex field of machine learning (ML) and predictive analytics. For this, we selected Amazon S3, known for its scalability and security.

AWS 94

AWS ML ML Predictive Analytics 94

Snorkel AI

MARCH 9, 2023

Each k8s cluster is made up of two key components: the k8s control plane and an arbitrary number of attached worker nodes whose sole job is to run containers. The scheduler takes into account many factors, including: How busy are particular worker nodes? Upgrading/rotating underlying nodes. Do they have room for more pods?

Clustering 52

Clustering ML ML Data Scientist 52

Snorkel AI

MARCH 9, 2023

Each k8s cluster is made up of two key components: the k8s control plane and an arbitrary number of attached worker nodes whose sole job is to run containers. The scheduler takes into account many factors, including: How busy are particular worker nodes? Upgrading/rotating underlying nodes. Do they have room for more pods?

Clustering 52

Clustering ML ML Data Scientist 52