AWS Machine Learning Blog

JANUARY 4, 2024

One such area that is evolving is using natural language processing (NLP) to unlock new opportunities for accessing data through intuitive SQL queries. Instead of dealing with complex technical code, business users and data analysts can ask questions related to data and insights in plain language.

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AWS Machine Learning Blog

AUGUST 30, 2024

With the rapid growth of generative artificial intelligence (AI), many AWS customers are looking to take advantage of publicly available foundation models (FMs) and technologies. This includes Meta Llama 3, Meta’s publicly available large language model (LLM).

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AWS Machine Learning Blog

AUGUST 20, 2024

Natural language is ambiguous and imprecise, whereas data adheres to rigid schemas. For example, SQL queries can be complex and unintuitive for non-technical users. Handling complex queries involving multiple tables, joins, and aggregations makes it difficult to interpret user intent and translate it into correct SQL operations.

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AWS Machine Learning Blog

SEPTEMBER 19, 2023

Implementing a multi-modal agent with AWS consolidates key insights from diverse structured and unstructured data on a large scale. All this is achieved using AWS services, thereby increasing the financial analyst’s efficiency to analyze multi-modal financial data (text, speech, and tabular data) holistically.

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AWS Machine Learning Blog

AUGUST 22, 2024

Snowflake Arctic is a family of enterprise-grade large language models (LLMs) built by Snowflake to cater to the needs of enterprise users, exhibiting exceptional capabilities (as shown in the following benchmarks ) in SQL querying, coding, and accurately following instructions.

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Data Science 101

NOVEMBER 29, 2019

Amazon Athena and Aurora add support for ML in SQL Queries You can now invoke Machine Learning models right from your SQL Queries. Use Amazon Sagemaker to add ML predictions in Amazon QuickSight Amazon QuickSight, the AWS BI tool, now has the capability to call Machine Learning models.

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Flipboard

DECEMBER 6, 2023

needed to address some of these challenges in one of their many AI use cases built on AWS. In this post, we discuss a Q&A bot use case that Q4 has implemented, the challenges that numerical and structured datasets presented, and how Q4 concluded that using SQL may be a viable solution.

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AWS Machine Learning Blog

MARCH 14, 2024

We formulated a text-to-SQL approach where by a user’s natural language query is converted to a SQL statement using an LLM. The SQL is run by Amazon Athena to return the relevant data. Amazon Kendra uses natural language processing (NLP) to understand user queries and find the most relevant documents.

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AWS Machine Learning Blog

APRIL 24, 2024

With AWS generative AI services like Amazon Bedrock , developers can create systems that expertly manage and respond to user requests. It is hosted on Amazon Elastic Container Service (Amazon ECS) with AWS Fargate , and it is accessed using an Application Load Balancer. It serves as the data source to the knowledge base.

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AWS Machine Learning Blog

JUNE 25, 2024

Businesses can use LLMs to gain valuable insights, streamline processes, and deliver enhanced customer experiences. In addition, the generative business intelligence (BI) capabilities of QuickSight allow you to ask questions about customer feedback using natural language, without the need to write SQL queries or learn a BI tool.

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AWS Machine Learning Blog

DECEMBER 29, 2022

It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. AWS offers tools such as RStudio on SageMaker and Amazon Redshift to help tackle these challenges. I acknowledge that AWS CloudFormation might create IAM resources with custom names.

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AWS Machine Learning Blog

AUGUST 12, 2024

Furthermore, the democratization of AI and ML through AWS and AWS Partner solutions is accelerating its adoption across all industries. Splunk , an AWS Partner, offers a unified security and observability platform built for speed and scale.

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AWS Machine Learning Blog

DECEMBER 14, 2023

In line with this mission, Talent.com collaborated with AWS to develop a cutting-edge job recommendation engine driven by deep learning, aimed at assisting users in advancing their careers. The solution does not require porting the feature extraction code to use PySpark, as required when using AWS Glue as the ETL solution.

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AWS Machine Learning Blog

JUNE 13, 2023

The natural language capabilities allow non-technical users to query data through conversational English rather than complex SQL. The AI and language models must identify the appropriate data sources, generate effective SQL queries, and produce coherent responses with embedded results at scale.

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AWS Machine Learning Blog

NOVEMBER 1, 2024

Fine-tuning is a powerful approach in natural language processing (NLP) and generative AI , allowing businesses to tailor pre-trained large language models (LLMs) for specific tasks. This process involves updating the model’s weights to improve its performance on targeted applications. Sonnet across various tasks.

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AWS Machine Learning Blog

JUNE 26, 2024

This post is a follow-up to Generative AI and multi-modal agents in AWS: The key to unlocking new value in financial markets. Analysts need to learn new tools and even some programming languages such as SQL (with different variations). Delete the S3 buckets created by AWS CloudFormation and then delete the CloudFormation stack.

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Data Science Dojo

JULY 3, 2024

Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. Data Processing and Analysis : Techniques for data cleaning, manipulation, and analysis using libraries such as Pandas and Numpy in Python.

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AWS Machine Learning Blog

APRIL 17, 2023

For scenarios where you need to add your own custom scripts for data transformations, you can write your transformation logic in Pandas, PySpark, PySpark SQL. With the Data Wrangler custom transform capability, you can write your transformation logic in Pandas, PySpark, PySpark SQL. After notebook files (.ipynb)

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AWS Machine Learning Blog

SEPTEMBER 24, 2024

Working with the AWS Generative AI Innovation Center , DoorDash built a solution to provide Dashers with a low-latency self-service voice experience to answer frequently asked questions, reducing the need for live agent assistance, in just 2 months. “We You can deploy the solution in your own AWS account and try the example solution.

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AWS Machine Learning Blog

NOVEMBER 14, 2023

Source: Generative AI on AWS (O’Reilly, 2023) LoRA has gained popularity recently for several reasons. LLMs, like Llama2, have shown state-of-the-art performance on natural language processing (NLP) tasks when fine-tuned on domain-specific data. This method of separating the base and adapter models has some drawbacks.

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ODSC - Open Data Science

FEBRUARY 17, 2023

Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. Knowing some SQL is also essential.

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AWS Machine Learning Blog

OCTOBER 19, 2023

Amazon Comprehend is a natural language processing (NLP) service that uses ML to uncover insights and relationships in unstructured data, with no managing infrastructure or ML experience required. Prerequisites For this walkthrough, you should have the following: An AWS account. A SageMaker Studio domain and user.

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AWS Machine Learning Blog

MAY 25, 2023

Amazon Kendra is a highly accurate and intelligent search service that enables users to search unstructured and structured data using natural language processing (NLP) and advanced search algorithms. With Amazon Kendra, you can find relevant answers to your questions quickly, without sifting through documents.

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AWS Machine Learning Blog

SEPTEMBER 19, 2023

Explore the feature processing pipelines and lineage in Amazon SageMaker Studio. Prerequisites To follow this tutorial, you need the following: An AWS account. AWS Identity and Access Management (IAM) permissions. Define the aggregate() function to aggregate the data using PySpark SQL and user-defined functions (UDFs).

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AWS Machine Learning Blog

NOVEMBER 27, 2023

SageMaker Canvas provides a visual point-and-click interface to generate accurate ML predictions for classification, regression, forecasting, natural language processing (NLP), and computer vision (CV). Perform ANSI SQL queries on Salesforce Data Cloud data (Data Cloud_query_api ). For Callback URL , enter [link].studio.sagemaker.aws/canvas/default/lab

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Pickl AI

DECEMBER 25, 2024

Descriptive analytics is a fundamental method that summarizes past data using tools like Excel or SQL to generate reports. Techniques like Natural Language Processing (NLP) and computer vision are applied to extract insights from text and images. Data Scientists rely on technical proficiency.

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Alation

OCTOBER 14, 2021

As pioneers in the Natural Language Processing (NLP) space, Lyngo has leveled the data playing field with tools that allow anyone to learn from data. You don’t have to know SQL to query your data, and you don’t have to be an analyst to draw data-driven conclusions. Step two is where Lyngo and SQL come in.

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AWS Machine Learning Blog

APRIL 8, 2024

It provides tools that offer data connectors to ingest your existing data with various sources and formats (PDFs, docs, APIs, SQL, and more). Prerequisites For this example, you need an AWS account with a SageMaker domain and appropriate AWS Identity and Access Management (IAM) permissions.

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AWS Machine Learning Blog

FEBRUARY 28, 2023

AWS provides the most complete set of services for the entire end-to-end data journey for all workloads, all types of data, and all desired business outcomes. The high-level steps involved in the solution are as follows: Use AWS Step Functions to orchestrate the health data anonymization pipeline.

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Mlearning.ai

MAY 23, 2023

Familiarity with libraries like pandas, NumPy, and SQL for data handling is important. Check out this course to upskill on Apache Spark —  [link] Cloud Computing technologies such as AWS, GCP, Azure will also be a plus. This includes skills in data cleaning, preprocessing, transformation, and exploratory data analysis (EDA).

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AWS Machine Learning Blog

NOVEMBER 27, 2023

This could involve better preprocessing tools, semi-supervised learning techniques, and advances in natural language processing. You can create a custom transform using Pandas, PySpark, Python user-defined functions, and SQL PySpark. About the Authors Ajjay Govindaram is a Senior Solutions Architect at AWS.

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IBM Journey to AI blog

JULY 17, 2023

This allows users to accomplish different Natural Language Processing (NLP) functional tasks and take advantage of IBM vetted pre-trained open-source foundation models. Encoder-decoder and decoder-only large language models are available in the Prompt Lab today. To bridge the tuning gap, watsonx.ai

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ODSC - Open Data Science

AUGUST 15, 2023

Build Classification and Regression Models with Spark on AWS Suman Debnath | Principal Developer Advocate, Data Engineering | Amazon Web Services This immersive session will cover optimizing PySpark and best practices for Spark MLlib.

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Pickl AI

JANUARY 13, 2025

Proficiency in programming languages like Python and SQL. Key Skills Experience with cloud platforms (AWS, Azure). Familiarity with SQL for database management. Key Skills Proficiency in programming languages such as Python or Java. Salary Range: 12,00,000 – 35,00,000 per annum.

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phData

NOVEMBER 13, 2024

The Large Language Models (LLMs) have the ability to interpret and create from data, whether through natural language processing (NLP) or synthetic data generation, which can result in enriched data visualization. This section will focus on setting up AWS Bedrock and Snowflake Cortex in Matllion DPC.

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Mlearning.ai

JUNE 23, 2023

Relational databases (like MySQL) or No-SQL databases (AWS DynamoDB) can store structured or even semi-structured data but there is one inherent problem. Options (Free vs Paid) Closing Introduction In today’s increasingly globalized world, the ability to communicate in multiple languages has become a highly valuable skill.

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Women in Big Data

DECEMBER 9, 2024

Examples include SQl, DWH, and Cloud based systems (Google Bigquery). It integrates seamlessly with a wide range of data sources like Excel, Azure and SQL server, Salesforce, SAP Hana, IBM Netezza and CDP which makes it a compelling choice for businesses that have already invested in the Microsoft ecosystem.

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