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%. An important aspect of our strategy has been the use of SageMaker and AWS Batch to refine pre-trained BERT models for seven different languages.

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BERT Auto-complete Data Scientist Machine Learning 114

Unite.AI

FEBRUARY 21, 2024

For users who are unfamiliar with Airflow, can you explain what makes it the ideal platform to programmatically author, schedule and monitor workflows? Airflow also has many data integrations with popular databases, applications, and tools, as well as dozens of cloud services — and more are added every month.

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LLM Data Platform Software Engineer Chatbots 147

IBM Journey to AI blog

DECEMBER 16, 2022

An enterprise data catalog automates the process of contextualizing data assets by using: Business metadata to describe an asset’s content and purpose. A business glossary to explain the business terms used within a data asset. This is especially helpful when handling massive amounts of big data.

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Metadata Data Quality Data Discovery Data Scientist 130

The MLOps Blog

JUNE 27, 2023

This includes features for model explainability, fairness assessment, privacy preservation, and compliance tracking. Integration with ML tools and libraries: Provide you with flexibility and extensibility. An integrated model factory to develop, deploy, and monitor models in one place using your preferred tools and languages.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

Pickl AI

APRIL 29, 2024

A DBMS is a software application that helps create, store, manage, and retrieve data in a structured and efficient way. It acts as a central repository for data, ensuring data integrity, security, and accessibility. DELETE : Removes data from a table. Explain the concept of normalization in DBMS.

Data Integration 52

Data Integration Explainability Categorization Big Data 52

Pickl AI

OCTOBER 9, 2023

The Solution: XYZ Retail embarked on a transformative journey by integrating Machine Learning into its demand forecasting strategy. Retailers must ensure data is clean, consistent, and free from anomalies. Consistently review and purify data to uphold its accuracy. Invest in robust data integration to maximize insights.

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AWS Machine Learning Blog

OCTOBER 2, 2024

However, scaling up generative AI and making adoption easier for different lines of businesses (LOBs) comes with challenges around making sure data privacy and security, legal, compliance, and operational complexities are governed on an organizational level. Ask the model to self-explain , meaning provide explanations for their own decisions.

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AWS Machine Learning Blog

FEBRUARY 29, 2024

The form should explain all foreseeable risks, side effects, or discomforts you might experience from participating', 'What will participation involve? The form should explain all foreseeable risks, side effects, or discomforts you might experience from participating. strip() for item in response.strip().split("nn")[1:-1]

Machine Learning 131

Machine Learning Computer Vision Generative AI Explainability 131

AWS Machine Learning Blog

DECEMBER 7, 2023

Calculating courier requirements The first step is to estimate hourly demand for each warehouse, as explained in the Algorithm selection section. Solution overview The End-to-end Workforce Management Project (E2E Project) is a large-scale project and it can be described in three topics: 1.

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Convolutional Neural Networks Algorithm Neural Network Data Science 120

Heartbeat

OCTOBER 25, 2023

This integration requires sophisticated computational methods, such as data integration algorithms and network analysis approaches, which enable extracting meaningful insights from multiple layers of biological data.

Machine Learning 52

Machine Learning Data Scientist Convolutional Neural Networks Algorithm 52

Heartbeat

OCTOBER 23, 2023

Image from "Big Data Analytics Methods" by Peter Ghavami Here are some critical contributions of data scientists and machine learning engineers in health informatics: Data Analysis and Visualization: Data scientists and machine learning engineers are skilled in analyzing large, complex healthcare datasets.

Data Scientist 52

Data Scientist Machine Learning Big Data Algorithm 52

Pickl AI

JULY 23, 2023

While unstructured data may seem chaotic, advancements in artificial intelligence and machine learning enable us to extract valuable insights from this data type. Big Data Big data refers to vast volumes of information that exceed the processing capabilities of traditional databases.

Data Analysis 52

Data Analysis Explainability Algorithm Machine Learning 52

Pickl AI

FEBRUARY 10, 2025

Explain the Different Types of Cloud Services Offered by AWS. Amazon S3 (Simple Storage Service) is an object storage service that provides high durability and availability for data storage. Common use cases include: Backup and restore Data archiving Big Data Analytics Static website hosting 5. Amazon EC2).

Auto-complete 52

Auto-complete Explainability Big Data Automation 52

Marktechpost

JULY 23, 2023

Big data analytics are supported by scalable, object-oriented services. Each of the “buckets” used to store data has a maximum capacity of 5 terabytes. The platform’s schema independence allows you to directly consume data in any format or type. It will combine all of your data sources.

Machine Learning 52

Machine Learning Big Data ETL Data Integration 52

AWS Machine Learning Blog

JUNE 3, 2024

Perform an analysis on the transformed data Now that transformations have been done on the data, you may want to perform analyses to make sure they haven’t affected data integrity. He helps customers implement big data, machine learning, analytics solutions, and generative AI implementations.

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Generative AI Categorization Auto-complete Auto-classification 109

Marktechpost

JULY 17, 2023

The company’s H20 Driverless AI streamlines AI development and predictive analytics for professionals and citizen data scientists through open source and customized recipes. When necessary, the platform also enables numerous governance and explainability elements.

Machine Learning 98

Machine Learning Data Mining Data Scientist Data Science 98

Pickl AI

APRIL 26, 2024

Top 50+ Interview Questions for Data Analysts Technical Questions SQL Queries What is SQL, and why is it necessary for data analysis? SQL stands for Structured Query Language, essential for querying and manipulating data stored in relational databases. Data Visualisation What are the fundamental principles of data visualisation?

Data Analysis 52

Data Analysis Machine Learning ETL Explainability 52

Pickl AI

SEPTEMBER 5, 2024

Unified Data Services: Azure Synapse Analytics combines big data and data warehousing, offering a unified analytics experience. Azure’s global network of data centres ensures high availability and performance, making it a powerful platform for Data Scientists to leverage for diverse data-driven projects.

Data Scientist 52

Data Scientist Data Science Machine Learning Data Analysis 52

Pickl AI

JULY 18, 2024

In contrast, MongoDB uses a more straightforward query language that works well with JSON data structures. MongoDB’s horizontal scaling capabilities surpass relational databases’ typical vertical scaling limitations, making it suitable for big data applications. Explain The Difference Between MongoDB and SQL Databases.

Explainability 52

Explainability ETL Data Science Python 52

Unite.AI

JULY 5, 2024

Establishing strong information governance frameworks ensures data quality, security and regulatory compliance. This includes defining data standards, policies and processes for data management, as well as leveraging advanced analytics and big data technologies to extract actionable insights from health data.

Data Integration 147

Data Integration Data Quality Algorithm AI Modeling 147

Marktechpost

NOVEMBER 4, 2024

In order to solve particular business questions, this process usually includes developing and managing data systems, collecting and cleaning data, analyzing it statistically, and interpreting the findings. ThoughtSpot is a cloud-based solution that offers adjustable pricing to accommodate different requirements.

Data Analysis 83

Data Analysis Machine Learning Data Science Python 83

Marktechpost

NOVEMBER 1, 2024

By allowing users to chat with their data, DataLab’s AI Assistant further increases productivity by streamlining processes like coding, providing context-specific recommendations to improve workflow efficiency, and explaining data structures.

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Artificial Intelligence Artificial Intelligence AI Tools Machine Learning 97

AWS Machine Learning Blog

AUGUST 2, 2024

In this post, we explain how Cepsa Química and partner Keepler have implemented a generative AI assistant to increase the efficiency of the product stewardship team when answering compliance queries related to the chemical products they market. The following diagram illustrates this architecture.

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Generative AI LLM Machine Learning Data Scientist 111

AWS Machine Learning Blog

OCTOBER 24, 2024

Learn more in Amazon OpenSearch Service’s vector database capabilities explained. This enables you to preprocess your external data in the phases including cleaning, sanitization, chunking documents, generating vector embeddings for each chunk, and loading into a vector store. In his spare time, he enjoys cycling with his road bike.

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LLM Big Data Architect Big Data Software Development 111