AWS Machine Learning Blog

APRIL 23, 2024

SageMaker Studio Local Mode SageMaker Studio introduces Local Mode, enabling you to run SageMaker training, inference, batch transform, and processing jobs directly on your JupyterLab, Code Editor, or SageMaker Studio Classic notebook instances without requiring remote compute resources.

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IBM Data Science in Practice

MARCH 21, 2023

Action Detection : This is a video based ML model that detects and tags actions in a video. This may be a daunting task for a non-data scientist or a data scientist with little to no experience. The best part about this tool is that it offers a user-friendly low-code/no-code user interface to train and deploy complex models with ease!

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IBM Data Science in Practice

JANUARY 4, 2023

Probably, the last one would be asked only by an alien :D Problem Ingesting data in hourly structure is very efficient because the system just needs to create a new set of files for that hour when a new batch of data arrives. We have multiple systems that ingest, store and retrieve data. This means it creates 2¹³ = 8,192 partitions.

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Flipboard

OCTOBER 25, 2023

After decades of digitizing everything in your enterprise, you may have an enormous amount of data, but with dormant value. However, with the help of AI and machine learning (ML), new software tools are now available to unearth the value of unstructured data. Additionally, we show how to use AWS AI/ML services for analyzing unstructured data.

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AWS Machine Learning Blog

MAY 17, 2023

Run batch and single predictions using the multi-class model. Facies classification is the process of segmenting lithologic formations from geologic data at the wellbore location. During drilling, wireline logs are obtained, which have depth-dependent geologic information. For this post, we use data from the following open-source GitHub repo.

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AWS Machine Learning Blog

JANUARY 9, 2023

Machine learning (ML) applications are complex to deploy and often require the ability to hyper-scale, and have ultra-low latency requirements and stringent cost budgets. Use cases such as fraud detection, product recommendations, and traffic prediction are examples where milliseconds matter and are critical for business success.

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Flipboard

FEBRUARY 16, 2023

Solution overview AWS offers a wide variety of services for distributed model training or inferencing workloads at scale, including AWS Batch , Amazon Elastic Kubernetes Service (Amazon EKS), and UltraClusters. Modern model pre-training often calls for larger cluster deployment to reduce time and cost. The following diagram shows an example.

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AWS Machine Learning Blog

FEBRUARY 29, 2024

The framework code and examples presented here only cover model training pipelines, but can be readily extended to batch inference pipelines as well. The framework code and examples presented here only cover model training pipelines, but can be readily extended to batch inference pipelines as well.

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Towards AI

AUGUST 16, 2023

AI engineering is the discipline focused on developing tools, systems, and processes to enable the application of artificial intelligence in real-world contexts, which combines the principles of systems engineering, software engineering, and computer science to create AI systems. 85% or more of AI projects fail [1][2].

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AWS Machine Learning Blog

JULY 3, 2023

In computer vision (CV), adding tags to identify objects of interest or bounding boxes to locate the objects is called labeling. It’s one of the prerequisite tasks to prepare training data to train a deep learning model. Amazon SageMaker Ground Truth – Alternatively, you can manage your own data labeling workflows and workforce to label data.

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Applied Data Science

MAY 6, 2021

Building end-to-end data science solutions means developing data collection, feature engineering, model building and model serving processes. This is part of the Full Stack Data Scientist blog series. In short, it’s free, in pure Python, and it has a logical structure as well as a slick UI for management, logging and debugging.

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AWS Machine Learning Blog

OCTOBER 17, 2023

We adopt a third-party perspective and objective judgment to help customers sort out their value propositions, collect pain points, propose appropriate solutions, and create the most cost-effective and usable prototypes to help them systematically achieve their business goals. This method is called working backwards at AWS.

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AWS Machine Learning Blog

JANUARY 13, 2023

Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at a single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a centralized data repository. HCLS use case.

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Chatbots Life

SEPTEMBER 11, 2023

Introduction The article explores the practical application of essential Python libraries like TextBlob, symspell, pyspellchecker and Flan-T5 based grammar checker in the context of spell and grammar checking. Learning Objectives: In this article, we will understand the following: What are the spell checker and grammar checker?

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Snorkel AI

MARCH 14, 2023

Labeling unstructured data for ML projects has traditionally involved humans tagging each data point manually. Artificial intelligence is reshaping virtually every industry. And yet – despite AI’s potential – Gartner predicts that by 2024 half of current AI deployments will be either delayed or canceled outright.

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Snorkel AI

MARCH 14, 2023

Labeling unstructured data for ML projects has traditionally involved humans tagging each data point manually. Artificial intelligence is reshaping virtually every industry. And yet – despite AI’s potential – Gartner predicts that by 2024 half of current AI deployments will be either delayed or canceled outright.

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IBM Journey to AI blog

JULY 13, 2023

Data science tasks such as machine learning also greatly benefit from good data integrity. When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data.

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Smart Data Collective

MARCH 5, 2022

Even if you already have a full-time job in data science, you will be able to leverage your expertise as a big data expert to make extra money on the side. There are a lot of ways to capitalize off of your knowledge of data science. Ways that Data-Savvy People Can Make Money with Side Hustles This Year.

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DataRobot Blog

JUNE 16, 2022

We’re excited to announce DataRobot’s integration with Apache Airflow , a popular open source orchestration tool and workflow scheduler used by more than 12,000 organizations* across industries like financial services , healthcare , retail , and manufacturing. Integrate DataRobot and Apache Airflow for Retraining and Redeploying Models.

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AWS Machine Learning Blog

DECEMBER 13, 2023

Machine learning (ML) models do not operate in isolation. To deliver value, they must integrate into existing production systems and infrastructure, which necessitates considering the entire ML lifecycle during design and development. Building a robust MLOps pipeline demands cross-functional collaboration.

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The MLOps Blog

JUNE 27, 2023

As you delve into the landscape of MLOps in 2023, you will find a plethora of tools and platforms that have gained traction and are shaping the way models are developed, deployed, and monitored. MLOps landscape One of the defining characteristics of the MLOps landscape in 2023 is the coexistence of both open-source and closed-source solutions.

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AWS Machine Learning Blog

APRIL 25, 2023

Data scientists typically carry out several iterations of experimentation in data processing and training models while working on any ML problem. Data scientists typically carry out several iterations of experimentation in data processing and training models while working on any ML problem.

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Hacker News

MARCH 25, 2024

In the early 1980s, offices were noisy places, filled with the sound of metal striking inked ribbons to mark characters on paper. IBM Selectric typewriters clacked, daisy wheel printers clattered, and dot-matrix printers made loud ripping sounds. Today, those noises are gone. The main reason for the quiet? The inkjet printer.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

We are excited to share that Amazon SageMaker HyperPod is now generally available to enable training foundation models with thousands of accelerators up to 40% faster by providing a highly resilient training environment while eliminating the undifferentiated heavy lifting involved in operating large-scale training clusters.

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Mlearning.ai

MAY 23, 2023

Hey guys, in this blog we will see some of the most asked Data Science Interview Questions by interviewers in [year]. Data science has become an integral part of many industries, and as a result, the demand for skilled data scientists is soaring. Read the full blog here —  [link] Data Science Interview Questions for Freshers 1.

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AWS Machine Learning Blog

NOVEMBER 1, 2023

Visual language processing (VLP) is at the forefront of generative AI, driving advancements in multimodal learning that encompasses language intelligence, vision understanding, and processing. Their use cases span various domains, from media entertainment to medical diagnostics and quality assurance in manufacturing.

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Hacker News

FEBRUARY 14, 2023

See also: “Wolfram|Alpha as the Way to Bring Computational Knowledge Superpowers to ChatGPT” » It’s Just Adding One Word at a Time That ChatGPT can automatically generate something that reads even superficially like human-written text is remarkable, and unexpected. But how does it do it? And why does it work?

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The MLOps Blog

MARCH 21, 2023

Moving across the typical machine learning lifecycle can be a nightmare. From gathering and processing data to building models through experiments, deploying the best ones, and managing them at scale for continuous value in production—it’s a lot. To do that, you’d need to take a systematic approach to MLOps —enter platforms!

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The MLOps Blog

DECEMBER 7, 2022

There’s an old saying in Argentina that goes: “A río revuelto, ganancia de pescadores”. This translates to “ when the rivers are stirred, the fishermen profit ”. 2022 will be remembered as a defining year for the crypto ecosystem. And that includes data. Those were the questions that the guys at CTF Capital —a trading fund— had.

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The MLOps Blog

NOVEMBER 30, 2022

Data science practitioners experiment with algorithms, data, and hyperparameters to develop a model that generates business insights. It will further build upon the need to compare experiments that call for reproducibility, visibility, and collaboration across the board in data science teams. across industries and domains.

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AWS Machine Learning Blog

FEBRUARY 20, 2023

Today, we announce that you can personalize the image generation model to your use case by fine-tuning it on your custom dataset in Amazon SageMaker JumpStart. This can be useful when creating art, logos, custom designs, NFTs, and so on, or fun stuff such as generating custom AI images of your pets or avatars of yourself.

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Explosion

AUGUST 3, 2017

The experiments can’t begin until the first batch of annotations are complete, but the annotation team can’t start until they receive the annotation manuals. Data science projects are said to have uneven returns, like start-ups: a minority of projects are very successful, recouping costs for a larger number of failures.

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AWS Machine Learning Blog

AUGUST 4, 2023

This post is co-authored by Daryl Martis, Director of Product, Salesforce Einstein AI. This is the second post in a series discussing the integration of Salesforce Data Cloud and Amazon SageMaker. The endpoints are then registered to the Salesforce Data Cloud to activate predictions in Salesforce. We use the following sample dataset.

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The MLOps Blog

AUGUST 3, 2023

This article was originally an episode of the ML Platform Podcast , a show where Piotr Niedźwiedź and Aurimas Griciūnas, together with ML platform professionals, discuss design choices, best practices, example tool stacks, and real-world learnings from some of the best ML platform professionals. Stefan: Yeah. Thanks for having me. What is DAGWorks?

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The MLOps Blog

OCTOBER 3, 2023

Mikiko Bazeley: Most people are really surprised to hear that my background in college was not computer science. In this episode, Mikiko Bazeley shares her learnings from building the ML Platform at Mailchimp. With us today on the episode is our guest, Mikiko Bazeley. Mikiko is a very well-known figure in the data community.

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Snorkel AI

MAY 25, 2023

Since the public unveiling of ChatGPT, large language models (or LLMs) have had a cultural moment. The potential of these enormous neural networks has both excited and frightened the public; the same technology that promises to help you digest long email chains also threatens to dethrone the essay as the default classroom assignment.

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Snorkel AI

MAY 25, 2023

Since the public unveiling of ChatGPT, large language models (or LLMs) have had a cultural moment. The potential of these enormous neural networks has both excited and frightened the public; the same technology that promises to help you digest long email chains also threatens to dethrone the essay as the default classroom assignment.

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