AWS Machine Learning Blog

NOVEMBER 29, 2023

Data preparation is a crucial step in any machine learning (ML) workflow, yet it often involves tedious and time-consuming tasks. Amazon SageMaker Canvas now supports comprehensive data preparation capabilities powered by Amazon SageMaker Data Wrangler.

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Flipboard

MARCH 3, 2023

Data proliferation has become a norm and as organizations become more data driven, automating data pipelines that enable data ingestion, curation, …

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AWS Machine Learning Blog

MARCH 3, 2023

Machine learning (ML) can help companies make better business decisions through advanced analytics. Companies across industries apply ML to use cases such as predicting customer churn, demand forecasting, credit scoring, predicting late shipments, and improving manufacturing quality. He is very passionate about data-driven AI.

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AWS Machine Learning Blog

JANUARY 26, 2023

Amazon SageMaker is a fully managed machine learning (ML) service providing various tools to build, train, optimize, and deploy ML models. ML insights facilitate decision-making. To assess the risk of credit applications, ML uses various data sources, thereby predicting the risk that a customer will be delinquent.

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AWS Machine Learning Blog

MAY 10, 2023

Quick iteration and faster time-to-value can be achieved by providing these analysts with a visual business intelligence (BI) tool for simple analysis, supported by technologies like machine learning (ML). Through this capability, ML becomes more accessible to business teams so they can accelerate data-driven decision-making.

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Data Science Dojo

SEPTEMBER 5, 2024

Artificial Intelligence (AI) and Machine Learning : Develop models that can learn from data and make autonomous decisions. Big Data Analysis : Processes and analyzes large datasets to extract meaningful insights. Healthcare : Improves patient outcomes through predictive analytics and personalized medicine. As per the U.S.

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Data Science Dojo

SEPTEMBER 5, 2024

Artificial Intelligence (AI) and Machine Learning : Develop models that can learn from data and make autonomous decisions. Big Data Analysis : Processes and analyzes large datasets to extract meaningful insights. Healthcare : Improves patient outcomes through predictive analytics and personalized medicine. As per the U.S.

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Smart Data Collective

APRIL 8, 2020

Data warehousing also facilitates easier data mining, which is the identification of patterns within the data which can then be used to drive higher profits and sales. There are several companies in the technological sphere making significant strides in advancing data warehousing technologies.

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Dataconomy

JULY 4, 2023

Hyper automation, which uses cutting-edge technologies like AI and ML, can help you automate even the most complex tasks. It’s also about using AI and ML to gain insights into your data and make better decisions. ML algorithms enable systems to identify patterns, make predictions, and take autonomous actions.

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AWS Machine Learning Blog

APRIL 19, 2023

Businesses are increasingly using machine learning (ML) to make near-real-time decisions, such as placing an ad, assigning a driver, recommending a product, or even dynamically pricing products and services. As a result, some enterprises have spent millions of dollars inventing their own proprietary infrastructure for feature management.

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Pickl AI

DECEMBER 26, 2024

Summary: “Data Science in a Cloud World” highlights how cloud computing transforms Data Science by providing scalable, cost-effective solutions for big data, Machine Learning, and real-time analytics. In Data Science in a Cloud World, we explore how cloud computing has revolutionised Data Science.

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AWS Machine Learning Blog

AUGUST 21, 2024

Amazon DataZone makes it straightforward for engineers, data scientists, product managers, analysts, and business users to access data throughout an organization so they can discover, use, and collaborate to derive data-driven insights.

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AWS Machine Learning Blog

DECEMBER 4, 2023

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. This capability of predictive analytics, particularly the accurate forecast of product categories, has proven invaluable.

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AWS Machine Learning Blog

FEBRUARY 21, 2025

Previously, he was a Data & Machine Learning Engineer at AWS, where he worked closely with customers to develop enterprise-scale data infrastructure, including data lakes, analytics dashboards, and ETL pipelines.

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AWS Machine Learning Blog

NOVEMBER 8, 2023

The compounded energy savings from optimizing code that customers run in certain data centers is even further compounded when we take into consideration that cloud providers such as AWS have dozens of data centers around the world. He works with strategic customers who are using AI/ML to solve complex business problems.

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AWS Machine Learning Blog

FEBRUARY 13, 2024

Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, share, and manage features for machine learning (ML) models. Features are inputs to ML models used during training and inference. SageMaker Feature Store now makes it effortless to share, discover, and access feature groups across AWS accounts.

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AWS Machine Learning Blog

SEPTEMBER 3, 2024

This allows SageMaker Studio users to perform petabyte-scale interactive data preparation, exploration, and machine learning (ML) directly within their familiar Studio notebooks, without the need to manage the underlying compute infrastructure. This same interface is also used for provisioning EMR clusters. python3.11-pip

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Dataconomy

APRIL 18, 2023

Parallel processing can help to improve the performance of these applications by distributing tasks among multiple processors and reducing the processing time required to render graphics or process multimedia data. As we’ve seen, parallel processing has the potential to revolutionize the way we process data and solve complex problems.

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AWS Machine Learning Blog

DECEMBER 7, 2023

Amazon Forecast is a fully managed service that uses machine learning (ML) algorithms to deliver highly accurate time series forecasts. Initially, daily forecasts for each country are formulated through ML models. He joined Getir in 2019 and currently works as a Senior Data Science & Analytics Manager.

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ODSC - Open Data Science

MARCH 6, 2023

Big data analytics is evergreen, and as more companies use big data it only makes sense that practitioners are interested in analyzing data in-house. Deep learning is a fairly common sibling of machine learning, just going a bit more in-depth, so ML practitioners most often still work with deep learning.

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Smart Data Collective

FEBRUARY 20, 2022

Whether it’s data management, analytics, or scalability, AWS can be the top-notch solution for any SaaS company. Also, AWS data protection services provide encryption and key management, as well as threat detection for continuous monitoring and protection of your accounts and workloads. Conclusions.

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AWS Machine Learning Blog

JUNE 3, 2024

Solution overview SageMaker Canvas brings together a broad set of capabilities to help data professionals prepare, build, train, and deploy ML models without writing any code. SageMaker Data Wrangler has also been integrated into SageMaker Canvas, reducing the time it takes to import, prepare, transform, featurize, and analyze data.

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Flipboard

MARCH 22, 2023

Snowflake is an AWS Partner with multiple AWS accreditations, including AWS competencies in machine learning (ML), retail, and data and analytics. Data scientist experience In this section, we cover how data scientists can connect to Snowflake as a data source in Data Wrangler and prepare data for ML.

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AWS Machine Learning Blog

MARCH 10, 2023

Amazon SageMaker Data Wrangler reduces the time it takes to aggregate and prepare data for machine learning (ML) from weeks to minutes in Amazon SageMaker Studio. Starting today, you can connect to Amazon EMR Hive as a big data query engine to bring in large datasets for ML.

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AWS Machine Learning Blog

MAY 15, 2023

Getir used Amazon Forecast , a fully managed service that uses machine learning (ML) algorithms to deliver highly accurate time series forecasts, to increase revenue by four percent and reduce waste cost by 50 percent. He joined Getir in 2019 and currently works as a Senior Data Science & Analytics Manager.

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AWS Machine Learning Blog

MAY 3, 2023

For any machine learning (ML) problem, the data scientist begins by working with data. This includes gathering, exploring, and understanding the business and technical aspects of the data, along with evaluation of any manipulations that may be needed for the model building process.

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Flipboard

MARCH 7, 2023

Amazon SageMaker Studio is a web-based, integrated development environment (IDE) for machine learning (ML) that lets you build, train, debug, deploy, and monitor your ML models. Studio provides all the tools you need to take your models from data preparation to experimentation to production while boosting your productivity.

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Heartbeat

OCTOBER 23, 2023

The Role of Data Scientists and ML Engineers in Health Informatics At the heart of the Age of Health Informatics are data scientists and ML engineers who play a critical role in harnessing the power of data and developing intelligent algorithms. Another notable application is predictive analytics in healthcare.

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AWS Machine Learning Blog

AUGUST 22, 2023

Machine learning (ML) is revolutionizing solutions across industries and driving new forms of insights and intelligence from data. Many ML algorithms train over large datasets, generalizing patterns it finds in the data and inferring results from those patterns as new unseen records are processed.

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Precisely

DECEMBER 20, 2022

Read more > #4 4 Real-World Examples of Financial Institutions Making Use of Big Data Big data has moved beyond “new tech” status and into mainstream use. Within the financial industry, there are some specialized uses for data integration and big data analytics.

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AWS Machine Learning Blog

NOVEMBER 27, 2023

Specifically, we clean the data and create RAG artifacts to answer the questions about the content of the dataset. Consider the following machine learning (ML) problem: user asks a large language model (LLM) question: “How to filter and search models in Amazon Bedrock?”. Further, we show how to preprocess a dataset for RAG.

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ODSC - Open Data Science

FEBRUARY 8, 2024

EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI.

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ODSC - Open Data Science

OCTOBER 22, 2024

Ali Arsanjani Dr. Ali Arsanjani, Director of Applied AI Engineering and Head of the AI Center of Excellence at Google Cloud, will share his expertise in Generative AI, Data/Analytics, and Predictive AI/ML. Snowflake: Known for its cloud-based data warehousing solutions, enabling efficient big data analytics.

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Pickl AI

JULY 2, 2023

Companies are constantly seeking ways to harness the power of data and implement the same in the decision-making process. Amidst all the new developments, data bricks have emerged as a unified analytics platform. What is Databricks? It is a unified analytics platform that simplifies building big data and AI solutions.

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ODSC - Open Data Science

FEBRUARY 6, 2024

EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI.

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Alation

OCTOBER 5, 2021

Why is your data governance strategy failing? According to the Gartner report, The State of Data and Analytics Governance Is Worse Than You Think , approximately 80% of businesses readily acknowledge that high-quality data governance is essential to achieving long-term business goals, objectives, and outcomes.

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IBM Journey to AI blog

MARCH 20, 2024

Low code helps businesses streamline workflows and accelerate the development of websites and mobile apps, the integration of external plugins, and cloud-based next-gen technologies, like artificial intelligence (AI) and machine learning (ML).

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