Dataconomy

FEBRUARY 21, 2024

Groq AI, a pioneering company in the AI chip industry, is setting the stage for a significant shift in how we perceive artificial intelligence processing power. a company founded in 2019 by a team of experienced software engineers and data scientists. What is Groq AI?

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PyImageSearch

JANUARY 15, 2024

Home Table of Contents Adversarial Learning with Keras and TensorFlow (Part 2): Implementing the Neural Structured Learning (NSL) Framework and Building a Data Pipeline Adversarial Learning with NSL CIFAR-10 Dataset Configuring Your Development Environment Need Help Configuring Your Development Environment? We open our config.py

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DataRobot Blog

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. Set up a data pipeline that delivers predictions to HubSpot and automatically initiate offers within the business rules you set.

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Alation

MAY 16, 2023

But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines. What is a Data Pipeline? A data pipeline is a series of processing steps that move data from its source to its destination. The answer?

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Data Pipeline Data Governance Data Lakes Data Warehouse 40

Pickl AI

DECEMBER 26, 2024

Key Features Tailored for Data Science These platforms offer specialised features to enhance productivity. Managed services like AWS Lambda and Azure Data Factory streamline data pipeline creation, while pre-built ML models in GCPs AI Hub reduce development time. Below are key strategies for achieving this.

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IBM Journey to AI blog

OCTOBER 22, 2024

Data is the differentiator as business leaders look to utilize their competitive edge as they implement generative AI (gen AI). Leaders feel the pressure to infuse their processes with artificial intelligence (AI) and are looking for ways to harness the insights in their data platforms to fuel this movement.

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Dataconomy

JANUARY 24, 2025

Then I lead data science projectsdesigning models, laying out data pipelines, and making sure everything is tested thoroughly. First, I help organizations figure out where AI can really make a difference, whether thats optimizing supply chains or personalizing customer experiences.

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ODSC - Open Data Science

DECEMBER 14, 2023

Photo Mosaics with Nearest Neighbors: Machine Learning for Digital Art In this post, we focus on a color-matching strategy that is of particular interest to a data science or machine learning audience because it utilizes a K-nearest neighbors (KNN) modeling approach.

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Flipboard

SEPTEMBER 25, 2023

(Y Combinator Photo) Seattle-area startups that just graduated from Y Combinator’s summer 2023 batch are tackling a wide range of problems — with plenty of help from artificial intelligence. Neum AI, a platform designed to assist companies in maintaining the relevancy of their AI applications with the latest data.

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Data Science Dojo

FEBRUARY 20, 2023

It is used by businesses across industries for a wide range of applications, including fraud prevention, marketing automation, customer service, artificial intelligence (AI), chatbots, virtual assistants, and recommendations. It provides a variety of tools for data engineering, including model training and deployment.

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Precisely

FEBRUARY 20, 2025

Follow five essential steps for success in making your data AI ready with data integration. Define clear goals, assess your data landscape, choose the right tools, ensure data quality and governance, and continuously optimize your integration processes.

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Data Science Dojo

APRIL 16, 2024

The field of artificial intelligence is booming with constant breakthroughs leading to ever-more sophisticated applications. As AI integrates into everything from healthcare to finance, new professions are emerging, demanding specialists to develop, manage, and maintain these intelligent systems.

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AWS Machine Learning Blog

FEBRUARY 1, 2024

Data pipelines In cases where you need to provide contextual data to the foundation model using the RAG pattern, you need a data pipeline that can ingest the source data, convert it to embedding vectors, and store the embedding vectors in a vector database.

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ODSC - Open Data Science

DECEMBER 5, 2023

On Wednesday, Peter Norvig, PhD, Engineering Director at Google and Education Fellow at the Stanford Institute for Human-Centered Artificial Intelligence (HAI) spoke about the human side of AI and how we can focus on using AI for the greater good, improving all stakeholders’ lives and the needs of all users.

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IBM Data Science in Practice

MARCH 8, 2023

Source: IBM Cloud Pak for Data Feature Computation Engine Users can transform batch, streaming, and real-time data into features Source: IBM Cloud Pak for Data To productionize a machine learning system, it is necessary to process new data continuously. Spark, Flink, etc.) How to Get Started?

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Applied Data Science

AUGUST 2, 2021

Automation Automating data pipelines and models ➡️ 6. The Data Engineer Not everyone working on a data science project is a data scientist. Data engineers are the glue that binds the products of data scientists into a coherent and robust data pipeline.

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ODSC - Open Data Science

FEBRUARY 17, 2023

Cloud Computing, APIs, and Data Engineering NLP experts don’t go straight into conducting sentiment analysis on their personal laptops. Data Engineering Platforms Spark is still the leader for data pipelines but other platforms are gaining ground.

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ODSC - Open Data Science

OCTOBER 15, 2023

AI is quickly scaling through dozens of industries as companies, non-profits, and governments are discovering the power of artificial intelligence. This can be helpful for businesses that need to track data from multiple sources, such as sales, marketing, and customer service. So, what are you waiting for?

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IBM Journey to AI blog

AUGUST 12, 2024

Instead, businesses tend to rely on advanced tools and strategies—namely artificial intelligence for IT operations (AIOps) and machine learning operations (MLOps)—to turn vast quantities of data into actionable insights that can improve IT decision-making and ultimately, the bottom line.

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ODSC - Open Data Science

DECEMBER 19, 2023

The field of artificial intelligence is growing rapidly and with it the demand for professionals who have tangible experience in AI and AI-powered tools. Data Engineer Data engineers are responsible for the end-to-end process of collecting, storing, and processing data. billion in 2021 to $331.2 billion by 2026.

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AWS Machine Learning Blog

JUNE 18, 2024

More than 170 tech teams used the latest cloud, machine learning and artificial intelligence technologies to build 33 solutions. With AWS Glue custom connectors, it’s effortless to transfer data between Amazon S3 and other applications.

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IBM Journey to AI blog

FEBRUARY 26, 2024

Increased data pipeline observability As discussed above, there are countless threats to your organization’s bottom line. That’s why data pipeline observability is so important. It not only protects your organization but also your customers who trust you with their money.

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AWS Machine Learning Blog

DECEMBER 4, 2024

It seems straightforward at first for batch data, but the engineering gets even more complicated when you need to go from batch data to incorporating real-time and streaming data sources, and from batch inference to real-time serving. Without the capabilities of Tecton , the architecture might look like the following diagram.

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Flipboard

FEBRUARY 13, 2023

Project Structure Creating Our Configuration File Creating Our Data Pipeline Preprocessing Faces: Detection and Cropping Summary Citation Information Building a Dataset for Triplet Loss with Keras and TensorFlow In today’s tutorial, we will take the first step toward building our real-time face recognition application. The dataset.py

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IBM Journey to AI blog

MAY 20, 2024

Implement data lineage tooling and methodologies: Tools are available that help organizations track the lineage of their data sets from ultimate source to target by parsing code, ETL (extract, transform, load) solutions and more. Your data scientists, executives and customers will thank you!

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AWS Machine Learning Blog

FEBRUARY 24, 2023

Solution overview In brief, the solution involved building three pipelines: Data pipeline – Extracts the metadata of the images Machine learning pipeline – Classifies and labels images Human-in-the-loop review pipeline – Uses a human team to review results The following diagram illustrates the solution architecture.

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Data Science Dojo

JULY 3, 2024

Data Engineering : Building and maintaining data pipelines, ETL (Extract, Transform, Load) processes, and data warehousing. Artificial Intelligence : Concepts of AI include neural networks, natural language processing (NLP), and reinforcement learning.

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IBM Journey to AI blog

MARCH 4, 2024

We have all been witnessing the transformative power of generative artificial intelligence (AI), with the promise to reshape all aspects of human society and commerce while companies simultaneously grapple with acute business imperatives. Financial/criminal: Violations of existing and emerging data and AI regulations.

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ODSC - Open Data Science

JUNE 19, 2023

There is no doubt that real-time operating systems (RTOS) have an important role in the future of big data collection and processing. How does RTOS help advance big data processing? Advanced analytics and AI  — It is virtually impossible to extract insights from big data through conventional evaluation and analysis, let alone manually.

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Precisely

APRIL 11, 2024

The project’s first phase focused on leveraging data replication offered by Precisely to enable near real-time replication of midrange data to AWS with support for heterogeneous source and target databases.

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AWS Machine Learning Blog

MARCH 14, 2024

Generative artificial intelligence (generative AI) has enabled new possibilities for building intelligent systems. Given the data sources, LLMs provided tools that would allow us to build a Q&A chatbot in weeks, rather than what may have taken years previously, and likely with worse performance.

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How to Learn Machine Learning

DECEMBER 24, 2024

You can easily: Store and process data using S3 and RedShift Create data pipelines with AWS Glue Deploy models through API Gateway Monitor performance with CloudWatch Manage access control with IAM This integrated ecosystem makes it easier to build end-to-end machine learning solutions.

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PyImageSearch

MARCH 20, 2023

Jump Right To The Downloads Section Training and Making Predictions with Siamese Networks and Triplet Loss In the second part of this series, we developed the modules required to build the data pipeline for our face recognition application. Figure 1: Overview of our Face Recognition Pipeline (source: image by the author).

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Dataconomy

MAY 16, 2023

With the explosion of big data and advancements in computing power, organizations can now collect, store, and analyze massive amounts of data to gain valuable insights. Machine learning, a subset of artificial intelligence , enables systems to learn and improve from data without being explicitly programmed.

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AWS Machine Learning Blog

OCTOBER 18, 2023

Purina used artificial intelligence (AI) and machine learning (ML) to automate animal breed detection at scale. Tayo Olajide is a seasoned Cloud Data Engineering generalist with over a decade of experience in architecting and implementing data solutions in cloud environments.

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Towards AI

MAY 30, 2024

Build and Run Data Pipelines with Sagemaker Pipelines by Jake Teo This article shows how to run long-running, repetitive, centrally managed, and traceable data pipelines leveraging AWS’s MLOps platform, Sagemaker, and its underlying services, Sagemaker pipelines, and Studio.

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Pickl AI

DECEMBER 25, 2024

Introduction In the rapidly evolving field of Artificial Intelligence , datasets like the Pile play a pivotal role in training models to understand and generate human-like text. The dataset is openly accessible, making it a go-to resource for researchers and developers in Artificial Intelligence.

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