AWS Machine Learning Blog

DECEMBER 4, 2023

In this post, we explain how we built an end-to-end product category prediction pipeline to help commercial teams by using Amazon SageMaker and AWS Batch , reducing model training duration by 90%. Overview of solution Five people from Getir’s data science team and infrastructure team worked together on this project.

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Mlearning.ai

JANUARY 26, 2023

What are the main bottlenecks of using EO data for data science projects in your organisation? (1/2) 1/2) What are the main bottlenecks of using EO data for data science projects in your organisation? (2/2) The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 43, 597–602. Marujo, R.

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AWS Machine Learning Blog

SEPTEMBER 29, 2023

Amazon SageMaker geospatial capabilities combined with Planet ’s satellite data can be used for crop segmentation, and there are numerous applications and potential benefits of this analysis to the fields of agriculture and sustainability. The analysis that inspired this post was originally written by Jennifer Reiber Kyle.

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Dataconomy

MARCH 1, 2024

Major online retailers like Amazon Kindle Direct Publishing offer access to a massive audience. Inkitt employs AI and data science to analyze the vast pool of self-published stories. The ArtStation protests erupted when the platform began featuring AI-generated images prominently alongside human-created art.

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AWS Machine Learning Blog

MAY 8, 2023

With Amazon SageMaker , you can manage the whole end-to-end machine learning (ML) lifecycle. By doing so, we can achieve robust and secure access to the MLflow server from both SageMaker managed infrastructure and Amazon SageMaker Studio , without having to worry about credentials and all the complexity behind credential management.

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AWS Machine Learning Blog

MAY 7, 2024

Rather than requiring extensive feature engineering and dataset labeling, LLMs can be fine-tuned on small amounts of domain-specific data to quickly adapt to new use cases. By handling most of the heavy lifting, services like Amazon SageMaker JumpStart remove the complexity of fine-tuning and deploying these models.

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Flipboard

AUGUST 17, 2023

. “The pace is crazy,” said Flying Fish principal Heather Gorham , speaking at a panel discussion about AI startups in Seattle this week. The panel discussion, at the TF Labs AI Summit, also featured Kevin Leneway , a software engineer at Pioneer Square Labs, and Larry Colagiovanni , a partner at Madrona Venture Labs.

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AWS Machine Learning Blog

JULY 31, 2023

Although machine learning (ML) can provide valuable insights, ML experts were needed to build customer churn prediction models until the introduction of Amazon SageMaker Canvas. Data preparation, feature engineering, and feature impact analysis are techniques that are essential to model building.

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ODSC - Open Data Science

AUGUST 9, 2023

In the unceasingly dynamic arena of data science, discerning and applying the right instruments can significantly shape the outcomes of your machine learning initiatives. A cordial greeting to all data science enthusiasts! We fill missing values in these new features with 0.0 and add them to our continuous columns.

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Data Science 101

NOVEMBER 22, 2019

Here are this week’s news and announcements related to Cloud Data Science. AWS Storage Day On November 20, 2019, Amazon held AWS Storage Day. S3 got some enhanced features. They allows devs to have the “ability to see, hear, speak, search, understand, and accelerate decision-making.” Announcements.

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AWS Machine Learning Blog

SEPTEMBER 6, 2023

Today, we are excited to announce the capability to fine-tune Llama 2 models by Meta using Amazon SageMaker JumpStart. Now you can also fine-tune 7 billion, 13 billion, and 70 billion parameters Llama 2 text generation models on SageMaker JumpStart using the Amazon SageMaker Studio UI with a few clicks or using the SageMaker Python SDK.

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Snorkel AI

JANUARY 12, 2023

In this article, we discuss key Snorkel Flow features and capabilities that help data science and machine learning teams to adapt NLP models to non-English languages. Machine learning models trained on labeled datasets generally learn from features in the available data to predict specific classes. There are exceptions to this!

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Dataconomy

APRIL 25, 2023

These tools use machine learning, natural language processing, computer vision, and other AI techniques to provide you with powerful features and functionalities. Wolfram Alpha can help students with math, science, engineering, history, geography, and more. Brainly uses AI to match students with the best answers and resources.

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The MLOps Blog

JULY 18, 2023

You have a bit of education in music composition, math, and science before you get more into the software engineering side of things. The funny thing about speech recognition is it’s really a two-stage pipeline: The first component of most speech recognition systems, at least historically, is extracting features.

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phData

JULY 18, 2023

Workloads like unstructured or semi-structured data processing, ML/generative AI operations, and custom data applications are all becoming expected features of today’s cloud data warehouse platforms. Its built-in features like data encryption and masking protect sensitive data throughout its lifecycle.

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Google Research AI blog

JANUARY 24, 2023

Further, this scale is being incorporated into features on our products, continuing a long line of our work to improve diversity and skin tone representation on Image Search and filters in Google Photos. The 10 shades of the Monk Skin Tone Scale.

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Alation

FEBRUARY 13, 2020

As well as innovation in the core product: new technology, a great design, and features that are really going to change the organizations accessing data to make better decisions. You see scale, obviously data science work in the cloud. John : What was the key learning as you guys went into this round of funding? Aaron : Absolutely.

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