Hacker News

MAY 2, 2024

This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. To get you started, author Jeroen Janssens provides a Docker image packed with over 100 Unix power tools—useful whether you work with Windows, macOS, or Linux.

Data Science 69

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IBM Journey to AI blog

FEBRUARY 29, 2024

Containers and Docker Container technology fundamentally changed in 2013 with Docker’s introduction and has continued unabated into this decade, steadily gaining in popularity and user acceptance. Docker is actually a Platform-as-a-Service (PaaS) and its main benefit is its flexibility.

Cloud Computing 84

Cloud Computing Artificial Intelligence Artificial Intelligence Clustering 84

Towards AI

FEBRUARY 18, 2024

Below is a comparison of Xinference with other model deployment and inference tools: Xinference supports two installation methods: Docker image and local installation. For those interested in the Docker method, please refer to the official Docker Installation Documentation. Here, we will focus on local installation.

Data Scientist 95

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Data Science Dojo

MAY 18, 2023

Learn the basics of Docker, including creating and running containers, working with images, automating image building using Dockerfile, and managing containers on your local machine and in production.

Data Science 195

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AWS Machine Learning Blog

MAY 15, 2024

All server management is done by AWS, providing many benefits such as automatic scaling and built-in high availability, letting you take your idea to production quickly. The Docker engine. Build the front-end using Streamlit and Docker You build two containers, one for generating exams and one for taking exams.

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Towards AI

APRIL 1, 2024

However, the transition to the “Engineering” phase, involving the deployment of these models into production environments, can be a tedious task for data scientists. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor. Join thousands of data leaders on the AI newsletter.

Data Science 96

Data Science Data Scientist Cloud Computing Deep Learning 96

Heartbeat

DECEMBER 27, 2023

Photo by Ian Taylor on Unsplash This article will comprehensively create, deploy, and execute machine learning application containers using the Docker tool. Lastly, it will discuss the best practices when working with Docker and the future of containerization. What is Docker? Docker is the most popular container technology.

Machine Learning 52

Machine Learning Machine Learning Python ML 52

Towards AI

JULY 20, 2023

Docker containers are one of the hottest trends in software development right now. In this tutorial, we will show you how you can dockerize easily a Flask API. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor. We will use this Python Rest API Example.

Python 88

Python AI AI Data Science 88

IBM Journey to AI blog

NOVEMBER 2, 2023

It was also in 2013 that Docker, a key player in Kubernetes history, came into the picture. Docker container technology uses the Linux kernel (the base component of the operating system) and features of the kernel to separate processes so they can run independently. Worker nodes run containers using container runtimes such as Docker.

Clustering 101

Clustering Cloud Computing AWS 101

The MLOps Blog

APRIL 5, 2023

Have you ever spent weeks or months building a machine learning model, only to later find out that deploying it into a production environment is complicated and time-consuming? The ultimate aim is to simplify the process of deploying a model, making the process of taking it to production seamless.

ML 69

ML ML Machine Learning Machine Learning 69

Towards AI

APRIL 3, 2024

Setting up the model server using Docker 2. The increased adoption and integration of LLMs across mainstream products further intensified the use cases and benefits of utilizing text data. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Data Profiling 94

Data Profiling AI AI Data Science 94

Flipboard

NOVEMBER 21, 2023

In recent years, MathWorks has brought many product offerings into the cloud, especially on Amazon Web Services (AWS). For more details about MathWorks cloud products, see MATLAB and Simulink in the Cloud or email Mathworks. Docker set up in an Amazon Elastic Compute Cloud (Amazon EC2) instance where MATLAB is running. Either

Machine Learning 116

Machine Learning Machine Learning AWS Decision Trees 116

phData

APRIL 18, 2024

Confluent offers a cloud version of Kafka, but for this demo, we will use the local version using a docker setup. Docker setup Kafka setup Snowflake account Snowflake Connector for Kafka Step 1: Confluent Docker Setup Docker is a platform designed to enable organizations to develop and build applications in containers.

Clustering 52

Clustering Data Engineering Data Engineer Data Engineering 52

AWS Machine Learning Blog

JUNE 23, 2023

For data scientists, moving machine learning (ML) models from proof of concept to production often presents a significant challenge. This post shows you how to easily deploy and run serverless ML inference by exposing your ML model as an endpoint using FastAPI, Docker, Lambda, and Amazon API Gateway.

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AWS ML ML Python 84

Tableau

JANUARY 26, 2021

As we start a new year, we’re excited to share important updates, including: Analytics extensions on Tableau Online, Tableau Server in a container, the new file format for Hyper API, and In-Product Extensions Gallery. Tableau Server in a Docker container is Tableau's first container-based server offering. In Tableau 2021.1, and 2020.1.1,

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Tableau Analytics Analytics Python 132

Mlearning.ai

FEBRUARY 28, 2023

Writing More Production-Ready Data Science Project (Part 2): Creating a Web App with Streamlit and Deploying to Google Cloud Run with Docker Photo by Venti Views on Unsplash 1. We will test the app locally before containerizing it with Docker and deploy it on Google Cloud Run to share with the world.

Data Science 52

Data Science Python ML ML 52

Tableau

JUNE 17, 2021

Product Management Senior Manager. you can now deploy and run Tableau Server for Linux using Docker containers and Kubernetes! Tableau Server in a Container ships as a tarball download which includes shell scripts that give you the ability to create Tableau Server Docker container images in your local environment. June 18, 2021.

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IBM Data Science in Practice

DECEMBER 7, 2022

You can serve the models on your laptop using Docker, which is useful when learning the technology or developing applications. Note that Docker will have to be logged in to the IBM Entitled Registry.) docker build. -t t watson-nlp-container:v1 This will create a Docker image named watson-nlp-container:v1.

Clustering 100

Clustering AI AI AWS 100

Applied Data Science

AUGUST 2, 2021

Data engineers are the glue that binds the products of data scientists into a coherent and robust data pipeline. They build production-ready systems using best-practice containerisation technologies, ETL tools and APIs. Git & Docker Coding is messy — it is rarely a linear process from idea to production ready system.

Data Science 130

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AWS Machine Learning Blog

APRIL 29, 2024

To build a production-grade AI system today (for example, to do multilingual sentiment analysis of customer support conversations), what are the primary technical challenges? Second, open source Metaflow provides the necessary software infrastructure to build production-grade ML/AI systems in a developer-friendly manner.

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AWS ML ML Python 93

Heartbeat

NOVEMBER 6, 2023

Image Source —  Pixel Production Inc In the previous article, you were introduced to the intricacies of data pipelines, including the two major types of existing data pipelines. This is because the installation process is more straightforward with docker, and you can easily roll back to the default state without issues.

Data Pipeline 52

Data Pipeline Clean Data ETL Python 52

Towards AI

JANUARY 27, 2024

Considering the current challenge, one potential solution involves building individual Docker images for each essential component — Streamlit UI, FastAPI server, and MLflow server. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor. From research to projects and ideas.

Machine Learning 85

Machine Learning Machine Learning Database Data Scientist 85

IBM Journey to AI blog

NOVEMBER 13, 2023

Docker was the first open-source software tool to popularize building, deploying and managing containerized applications. But Docker lacked an automated “orchestration” tool, which made it time-consuming and complex for data science teams to scale applications.

Machine Learning 109

Machine Learning Machine Learning ML ML 109

Mlearning.ai

SEPTEMBER 16, 2023

Simple and Pluggable production serving for production ML serving including prediction, pre/post-processing, monitoring, and explainability. We can see examples of the container build command and the container repository store command (here, docker hub) below.

Clustering 52

Clustering Python ML ML 52

Chatbots Life

MAY 22, 2023

Now let’s take a scenario: if we integrate OpenAI with an existing SaaS product, what would the result be? They have started understanding the pros and cons of AI with their SaaS products, like… Many chatbots are getting automated using AI. Docker is one of the strong examples of AI-powered products.

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AI AI AWS Data Science 98

Data Science Blog

NOVEMBER 8, 2022

Auf dem Computer, welcher zur Entwicklung verwendet werden soll, müssen Terraform, Google Cloud SDK, git, Docker und Python installiert sein. Terraform, Google Cloud SDK, Docker und Python müssen auf dem verwendeten Computer installiert werden, hierzu empfiehlt sich ein Paketmanager wie Homebrew oder Chocolatey. gunicorn --bind 0.0.0.0:8080

Python 130

Python Data Science Cloud Data 130

Mlearning.ai

FEBRUARY 6, 2023

Use SageMaker Processing Jobs to easily run inference on your large Dataset with Hugging Face’s Transformer Models Photo by Alex Kulikov on Unsplash This blog will give you a complete walk through of running a distributed batch inference on large data in production. Below is a sample DOCKER file. docker build -t ${algorithm_name}.

AWS 52

AWS ML ML Python 52

Dataconomy

APRIL 28, 2023

How to deploy a machine learning model in production? Machine learning model deployment involves making the trained model available for use in a production environment. Its primary functions include packaging and organizing docker containers to support the maintenance of an entire machine learning system.

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AWS Machine Learning Blog

JULY 24, 2023

For production workloads requiring high throughput and low latency, the selection of the Amazon Elastic Compute Cloud (EC2) instance, model serving stack, and deployment architecture is very important. Inefficient architecture can lead to suboptimal utilization of the accelerators and unnecessarily high production cost.

AWS 70

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Mlearning.ai

JULY 29, 2023

Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications II. Use your local computer with Docker engine installed to test the container run and make sure the expected behavior is observed (e.g., This can be done on an Azure Machine Learning compute, which comes with Docker and git installed.

Azure 52

Azure Machine Learning Machine Learning ML 52

Flipboard

MARCH 7, 2023

Studio provides all the tools you need to take your models from data preparation to experimentation to production while boosting your productivity. Configure a custom app image You must run this notebook as a SageMaker notebook instance to allow using Docker locally and run Docker commands in the notebook.

Python 93

Python AWS ML ML 93

Data Science Dojo

MARCH 9, 2023

Introduction It is a cumbersome and tiring process to install Docker first and then install Memphis. The flexibility, performance, and scalability provided by Azure virtual machine to Memphis make it possible to offer a production-ready message broker in under 3 minutes. Then look after the integration and dependency issues.

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phData

MAY 3, 2024

For example, in the retail industry, real-time analytics are constantly relied on to better stock shelves, understand customer demand, and maximize the sales of products (just to name a few). If unable to find it, look in the docker-desktop-data. Real-time analytics has real-time benefits.

Apache Kafka 52

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Towards AI

MARCH 6, 2024

ArangoDB offers the same functionality as Neo4j with more than competitive… arangodb.com In the course of this project, I set up a local instance of ArangoDB using docker, and employed the ArangoDB Python Driver, python-arango, to develop data ingestion scripts. Adjustments to this parameter are essential, especially in Docker environments.

Python 75

Python Database AI AI 75

Towards AI

FEBRUARY 8, 2024

With her unique blend of expertise in AI and a successful freelance career, Tina offers incredible insights into using AI to enhance your learning skills and productivity. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor. From research to projects and ideas.

AI 86

AI AI Machine Learning Machine Learning 86

Towards AI

APRIL 29, 2024

However, it will require you to set up Docker on your machine and be familiar with Docker containers. And, if you build a product using billions of vectors, Qdrant will scale smoothly. The distance metric can be a dot product, cosine similarity, Euclidean distance, or Manhattan distance. Click on the “Clusters” menu item.

Database 85

Database Clustering Python AI 85

AWS Machine Learning Blog

MAY 3, 2023

Primitive caching – We also implemented primitive caching for conv, matmul, and inner product operators to avoid redundant GEMM kernel initialization and tensor allocation overhead. amazonaws.com # Pull the AWS DLC for pytorch # Graviton docker pull 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference-graviton:2.0.0-cpu-py310-ubuntu20.04-ec2

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