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.

SQL 135

SQL Database AI AI 135

Data Science Dojo

MAY 18, 2023

Deep Learning with KNIME: This tutorial will provide theoretical and practical introductions to three deep learning topics using the KNIME Analytics Platform’s Keras Integration; first, how to configure and train an LSTM network for language generation; we’ll have some fun with this and generate fresh rap songs!

Data Science 195

Data Science AI AI SQL 195

Flipboard

DECEMBER 6, 2023

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. RAG with semantic search – Conventional RAG with semantic search was the last step before moving to SQL generation.

SQL 168

SQL Database AWS Machine Learning 168

AWS Machine Learning Blog

DECEMBER 6, 2023

Overview of RAG RAG solutions are inspired by representation learning and semantic search ideas that have been gradually adopted in ranking problems (for example, recommendation and search) and natural language processing (NLP) tasks since 2010.

SQL 120

SQL AWS Analytics Analytics 120

Data Science Blog

MAY 22, 2023

Neben den relationalen Datenbanken (SQL) gibt es auch die NoSQL -Datenbanken wie den Key-Value-Store, Dokumenten- und Graph-Datenbanken mit recht speziellen Anwendungsgebieten. In diesen geht nur leider dann doch irgendwann das Wissen verloren… Und das auch dann, wenn es nie aus ihnen herausgelöscht wird!

Deep Learning 244

Deep Learning Deep Learning Natural Language Processing AI 244

Data Science Dojo

AUGUST 18, 2023

Transformers are a type of neural network that are well-suited for natural language processing tasks. They are able to learn long-range dependencies between words, which is essential for understanding the nuances of human language. However, it can also be a time-consuming and computationally expensive process.

Natural Language Processing 195

Natural Language Processing Database AI AI 195

Data Science Dojo

JULY 3, 2024

Data Processing and Analysis : Techniques for data cleaning, manipulation, and analysis using libraries such as Pandas and Numpy in Python. Databases and SQL : Managing and querying relational databases using SQL, as well as working with NoSQL databases like MongoDB.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

phData

DECEMBER 7, 2023

In our previous article on Retrieval Augmented Generation (RAG), we discussed the need for a Vector Database to retrieve additional information for our prompts. Today, we will dive into the inner workings of a Vector Database to better understand exactly how this technology functions. What is a Vector Database in Simple Terms?

Database 52

Database Natural Language Processing Clustering SQL 52

Mlearning.ai

JUNE 17, 2023

Photo by Sneaky Elbow on Unsplash The advent of large language models (LLMs), such as OpenAI’s GPT-3, has ushered in a new era of possibilities in the realm of natural language processing. At present, there’s a growing buzz around Vector Databases. However, these new technologies bring their own set of challenges.

SQL 52

SQL Database Natural Language Processing Data Analyst 52

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.

Database 83

Database SQL AWS AI 83

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. The CloudFormation script created a database called sagemaker. Let’s populate this database with tables for the RStudio user to query. Loading data in Amazon Redshift Serverless.

AWS 121

AWS Machine Learning Machine Learning Natural Language Processing 121

AWS Machine Learning Blog

APRIL 24, 2024

We use Knowledge Bases for Amazon Bedrock to fetch from historical data stored as embeddings in the Amazon OpenSearch Service vector database. An LLM evaluates each question along with the chat history from the same session to determine its nature and which subject area it falls under (such as SQL, action, search, or SME).

AWS 126

AWS AI AI SQL 126

Dataconomy

OCTOBER 15, 2024

Natural Language Processing (NLP) for application design One of the most significant intersections between Gen AI and low-code development is through NLP. Developers can interact with LCNC platforms using natural language queries or prompts. Gen AI plays a pivotal role in automating these processes.

AI 128

AI AI Database Natural Language Processing 128

AWS Machine Learning Blog

MARCH 10, 2025

It was built using a combination of in-house and external cloud services on Microsoft Azure for large language models (LLMs), Pinecone for vectorized databases, and Amazon Elastic Compute Cloud (Amazon EC2) for embeddings. Amazon Bedrock Guardrails implements content filtering and safety checks as part of the query processing pipeline.

AWS 91

AWS Database AI AI 91

phData

NOVEMBER 28, 2024

“ Vector Databases are completely different from your cloud data warehouse.” – You might have heard that statement if you are involved in creating vector embeddings for your RAG-based Gen AI applications. Text splitting is breaking down a long document or text into smaller, manageable segments or “chunks” for processing.

Python 52

Python Database SQL Machine Learning 52

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.

SQL 120

SQL AWS AI AI 120

ODSC - Open Data Science

MARCH 3, 2025

Their work has set a gold standard for integrating advanced natural language processing (NLP ) into clinical settings. Speed: Handling large patient histories stretches GPT models, even with long context windows, and demands pre-optimized databases. Consistency: Variability in responses undermines clinician trust.

Natural Language Processing 52

Natural Language Processing Data Scientist SQL Database 52

Mlearning.ai

MAY 3, 2023

Vector Databases — Long Term Memory for AI Photo by Sven Brandsma on Unsplash Introduction In natural language processing (NLP), a vector is a mathematical representation of a word or text document. The Database One such solution for this problem is Elasticsearch. Conclusion So easy right!!

Database 52

Database AI AI Natural Language Processing 52

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.

AWS 118

AWS Natural Language Processing Machine Learning Machine Learning 118

AWS Machine Learning Blog

DECEMBER 14, 2023

Our pipeline belongs to the general ETL (extract, transform, and load) process family that combines data from multiple sources into a large, central repository. Multiple days of data can be processed by separate Processing jobs simultaneously. Employ AWS Glue for data crawling after processing multiple days of data.

ETL 99

ETL AWS ML ML 99

ODSC - Open Data Science

FEBRUARY 14, 2023

These models are the technology behind Open AI’s DALL-E and GPT-3 , and are powerful enough to understand natural language commands and generate high-quality code to instantly query databases. They can be fine-tuned on a smaller dataset to perform a specific task, such as language translation or summarization.

Database 124

Database AI AI Natural Language Processing 124

Applied Data Science

AUGUST 2, 2021

They bring deep expertise in machine learning , clustering , natural language processing , time series modelling , optimisation , hypothesis testing and deep learning to the team. The most common data science languages are Python and R   —  SQL is also a must have skill for acquiring and manipulating data.

Data Science 130

Data Science Data Scientist ML ML 130

AWS Machine Learning Blog

SEPTEMBER 19, 2023

For structured data, the agent uses the SQL Connector and SQLAlchemy to analyze databases, which includes Amazon Athena. Session(region_name=region_name) athena_client = session.client('athena') database=database_name table=table_Name. It can query a stocks database to answer questions on stocks.

AWS 120

AWS AI AI ML 120

AWS Machine Learning Blog

JUNE 26, 2024

Analysts need to learn new tools and even some programming languages such as SQL (with different variations). Action groups – Action groups are interfaces that an agent uses to interact with the different underlying components such as APIs and databases.

AWS 119

AWS AI AI Database 119

phData

SEPTEMBER 11, 2024

With Cortex Analyst from the Snowflake AI Data Cloud , business users can transform plain English questions into SQL queries, enabling self-service analytics and making data insights more accessible. This is especially powerful for users who may have pressing questions about their data but might not have the SQL-writing experience to do so.

SQL 52

SQL Natural Language Processing Database Data Analysis 52

Mlearning.ai

JUNE 23, 2023

A database that help index and search at blazing speed. Relational databases (like MySQL) or No-SQL databases (AWS DynamoDB) can store structured or even semi-structured data but there is one inherent problem. Unstructured data is hard to store in relational databases.

Database 52

Database ML ML Natural Language Processing 52

Pickl AI

JULY 18, 2023

Additionally, its natural language processing capabilities and Machine Learning frameworks like TensorFlow and scikit-learn make Python an all-in-one language for Data Science. SQL: Mastering Data Manipulation Structured Query Language (SQL) is a language designed specifically for managing and manipulating databases.

Data Science 52

Data Science SQL Data Scientist Python 52

The MLOps Blog

MAY 10, 2023

To ensure security and JSON/pickle benefits, you can save your model to a dedicated database. Next, you will see how you can save an ML model in a database. Storing ML models in a database There is also scope for you to save your ML models in relational databases PostgreSQL , MySQL , Oracle SQL , etc.

Python 105

Python ML ML Database 105

ODSC - Open Data Science

FEBRUARY 5, 2025

The Evolving AI Development Lifecycle Despite the revolutionary capabilities of LLMs, the core development lifecycle established by traditional natural language processing remains essential: Plan, Prepare Data, Engineer Model, Evaluate, Deploy, Operate, and Monitor. Previously, consultants spent weeks manually querying data.

Data Preparation 52

Data Preparation AI AI Data Scientist 52

ODSC - Open Data Science

MAY 11, 2023

Origins of Generative AI and Natural Language Processing with ChatGPT Joining in on the fun of using generative AI, we used ChatGPT to help us explore some of the key innovations over the past 50 years of AI. Databases for the Era of Artificial Intelligence Everyone is talking about ChatGPT.

AI 52

AI AI Data Science Azure 52

phData

MARCH 3, 2023

Whether you want nodes to publish your data to Tableau Server, connect to a Snowflake Data Cloud database , or perform image or audio analyses, there is an extension for you. If you need to connect to a database for any purpose, this extension cannot be ignored. These include Microsoft SQL Server, MySQL, Oracle, and PostgreSQL.

Database 52

Database Python Tableau Natural Language Processing 52

AWS Machine Learning Blog

NOVEMBER 27, 2023

This could involve better preprocessing tools, semi-supervised learning techniques, and advances in natural language processing. Access to Amazon OpenSearch as a vector database. The choice of vector database is an important architectural decision. Clean data is important for good model performance.

Data Preparation 88

Data Preparation AI AI Python 88

Pickl AI

FEBRUARY 18, 2025

It offers AI-driven analytics, including Natural Language Processing. Supports diverse data sources: Excel, SQL Server, Azure, and more. Also, it supports a wide range of data sources, including Excel spreadsheets, cloud services like Azure, and on-premises databases. Can Power BI Handle Real-Time Data?

Power BI 52

Power BI Azure Business Intelligence Business Intelligence 52

phData

FEBRUARY 10, 2023

This opens up a data engineer to create their transformation in Snowflake using python code instead of just SQL. Sentiment Analysis is a natural language processing (NLP) technique that tries to determine if data is positive or negative. Models are created via SQL or Python and can be materialized in various ways.

Python 59

Python Machine Learning Machine Learning SQL 59

ODSC - Open Data Science

MAY 25, 2023

His past roles have included work in analytics, big data, R, SQL, data mining, and more. Vargas’ responsibilities at Microsoft also include advisor to Microsoft CTO, AI scalability, and strategy expert, and lead for the organization’s AI at Scale Initiative and Azure Database Services. Looking for something a little sooner?

Data Science 52

Data Science Machine Learning Machine Learning Database 52

Pickl AI

JANUARY 13, 2025

Proficiency in programming languages like Python and SQL. Familiarity with SQL for database management. Key Skills Proficiency in programming languages such as Python or Java. Strong understanding of database management systems (e.g., Salary Range: 12,00,000 – 35,00,000 per annum.

AI 52

AI AI Machine Learning Machine Learning 52

The MLOps Blog

JUNE 27, 2023

For example, if your team works on recommender systems or natural language processing applications, you may want an MLOps tool that has built-in algorithms or templates for these use cases. Dolt Dolt is an open-source relational database system built on Git. Streaming pipelines to ingest and transform real-time data.

Machine Learning 134

Machine Learning Machine Learning ML ML 134