AWS Machine Learning Blog

NOVEMBER 18, 2024

In this post, we explain how InsuranceDekho harnessed the power of generative AI using Amazon Bedrock and Anthropic’s Claude to provide responses to customer queries on policy coverages, exclusions, and more. Continuous model enhancements – Amazon Bedrock provides access to a vast and continuously expanding set of FMs through a single API.

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Flipboard

NOVEMBER 20, 2024

Retrieval Augmented Generation (RAG) has become a crucial technique for improving the accuracy and relevance of AI-generated responses. The effectiveness of RAG heavily depends on the quality of context provided to the large language model (LLM), which is typically retrieved from vector stores based on user queries.

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Data Science Dojo

FEBRUARY 23, 2024

GPTs for Data science are the next step towards innovation in various data-related tasks. These are platforms that integrate the field of data analytics with artificial intelligence (AI) and machine learning (ML) solutions. What are GPTs for data science? This custom GPT is created by Open AI’s ChatGPT.

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Dataconomy

OCTOBER 15, 2024

With this wave, it brought an even more potent force: Generative AI, otherwise known as Gen AI, which changed the way developers (novice and expert) interact with LCNC platforms. This article discusses how gen AI is driving innovation in low-code software development, with regards to the technological aspects and implications.

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Pickl AI

JUNE 28, 2023

Data is driving most business decisions. In this, data modeling tools play a crucial role in developing and maintaining the information system. Moreover, it involves the creation of a conceptual representation of data and its relationship. Data modeling tools play a significant role in this.

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Flipboard

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Text, images, audio, and videos are common examples of unstructured data. Additionally, we show how to use AWS AI/ML services for analyzing unstructured data.

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IBM Journey to AI blog

AUGUST 7, 2023

Blockchain databases were designed to enhance trust in centralized ecosystems by incorporating tamper-evidence features into traditional databases. However, existing blockchain databases lack efficient tools for multiple parties to control shared data on the ledger.

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Data Science Dojo

MARCH 7, 2023

These skills include programming languages such as Python and R, statistics and probability, machine learning, data visualization, and data modeling. R is also popular among statisticians and data analysts, with libraries for data manipulation and machine learning.

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Pickl AI

FEBRUARY 23, 2023

Organisations must store data in a safe and secure place for which Databases and Data warehouses are essential. You must be familiar with the terms, but Database and Data Warehouse have some significant differences while being equally crucial for businesses. What is a Database? What is Data Warehouse?

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Towards AI

JULY 17, 2024

Author(s): Daniel Voyce Originally published on Towards AI. Photo by Steve Johnson on Unsplash It seems like everyone is currently talking about GraphRAG as the successor to RAG (Retrieval-Augmented Generation) in the Generative AI / LLM world right now. We use a graph database that is designed for it. What is RAG?

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Pickl AI

OCTOBER 21, 2024

Summary: This article highlights the significance of Database Management Systems in social media giants, focusing on their functionality, types, challenges, and future trends that impact user experience and data management. It handles the underlying operations and ensures efficient data processing.

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Pickl AI

JULY 8, 2024

Summary: Time series databases (TSDBs) are built for efficiently storing and analyzing data that changes over time. This data, often from sensors or IoT devices, is typically collected at regular intervals. Buckle up as we navigate the intricacies of storing and analysing this dynamic data.

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IBM Journey to AI blog

MARCH 29, 2024

Imagine a future where artificial intelligence (AI) seamlessly collaborates with existing supply chain solutions, redefining how organizations manage their assets. If you’re currently using traditional AI, advanced analytics, and intelligent automation, aren’t you already getting deep insights into asset performance?

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Data Science Dojo

FEBRUARY 23, 2024

Data science GPTs are the next step towards innovation in various data-related tasks. OpenAI’s GPT store is designed to make AI-powered solutions more accessible to different community members. However, our focus lies on exploring the data science GPTs available on the platform. What are data science GPTs?

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Data Science Dojo

FEBRUARY 23, 2024

GPTs for Data science are the next step towards innovation in various data-related tasks. These are platforms that integrate the field of data analytics with artificial intelligence (AI) and machine learning (ML) solutions. What are GPTs for data science? This custom GPT is created by Open AI’s ChatGPT.

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Iguazio

JULY 22, 2024

AI and generative Al can lead to major enterprise advancements and productivity gains. One popular gen AI use case is customer service and personalization. Gen AI chatbots have quickly transformed the way that customers interact with organizations. Another less obvious use case is fraud detection and prevention.

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phData

SEPTEMBER 19, 2023

However, to fully harness the potential of a data lake, effective data modeling methodologies and processes are crucial. Data modeling plays a pivotal role in defining the structure, relationships, and semantics of data within a data lake. Consistency of data throughout the data lake.

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IBM Journey to AI blog

MAY 29, 2024

As businesses strive to deliver cutting-edge solutions at an unprecedented pace, generative AI is poised to transform every stage of the software development lifecycle (SDLC). A McKinsey study shows that software developers can complete coding tasks up to twice as fast with generative AI.

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ODSC - Open Data Science

FEBRUARY 14, 2023

Trained with 570 GB of data from books and all the written text on the internet, ChatGPT is an impressive example of the training that goes into the creation of conversational AI. ChatGPT is a next-generation language model (referred to as GPT-3.5) But, like other large language models, it can be amusingly wrong.

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Towards AI

MARCH 20, 2024

Last Updated on March 25, 2024 by Editorial Team Author(s): Rajesh K Originally published on Towards AI. Graph databases and knowledge graphs are among the most widely adopted solutions for managing data represented as graphs, consisting of nodes (entities) and edges (relationships). This can pose a challenge for new users.

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Flipboard

JULY 24, 2023

It is also called the second brain as it can store data that is not arranged according to a present data model or schema and, therefore, cannot be stored in a traditional relational database or RDBMS. One of the open-source projects built by Stan Girar is Quivr.

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ODSC - Open Data Science

SEPTEMBER 27, 2023

In this article, we will delve into the concept of data lakes, explore their differences from data warehouses and relational databases, and discuss the significance of data version control in the context of large-scale data management. This ensures data consistency and integrity.

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phData

SEPTEMBER 27, 2024

Introduction: The Customer Data Modeling Dilemma You know, that thing we’ve been doing for years, trying to capture the essence of our customers in neat little profile boxes? For years, we’ve been obsessed with creating these grand, top-down customer data models. Yeah, that one.

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ODSC - Open Data Science

NOVEMBER 19, 2024

ODSC West 2024 showcased a wide range of talks and workshops from leading data science, AI, and machine learning experts. This blog highlights some of the most impactful AI slides from the world’s best data science instructors, focusing on cutting-edge advancements in AI, data modeling, and deployment strategies.

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IBM Journey to AI blog

OCTOBER 16, 2023

Artificial intelligence (AI) adoption is still in its early stages. As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. ” Are foundation models trustworthy?

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ODSC - Open Data Science

APRIL 6, 2023

It’s a foundational skill for working with relational databases Just about every data scientist or analyst will have to work with relational databases in their careers. So by learning to use SQL, you’ll write efficient and effective queries, as well as understand how the data is structured and stored.

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IBM Journey to AI blog

NOVEMBER 29, 2023

With the emergence of new advances and applications in machine learning models and artificial intelligence, including generative AI, generative adversarial networks, computer vision and transformers, many businesses are seeking to address their most pressing real-world data challenges using both types of synthetic data: structured and unstructured.

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Smart Data Collective

MAY 29, 2023

With these changes comes the challenge of understanding how to gather, manage, and make sense of the data collected in various markets. With the introduction and use of machine learning, AI tech is enabling greater efficiencies with respect to data and the insights embedded in the information.

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Dataconomy

SEPTEMBER 4, 2023

Key features of cloud analytics solutions include: Data models , Processing applications, and Analytics models. Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for business intelligence.

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IBM Journey to AI blog

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

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Iguazio

MAY 29, 2024

The generative AI industry is changing fast. New models and technologies (Hello GPT-4o) are emerging regularly, each more advanced than the last. They also need to understand regulatory and ethical implications of deploying AI models, taking into consideration issues like data privacy, security and ethical AI use.

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Pickl AI

OCTOBER 16, 2024

Summary: Relational Database Management Systems (RDBMS) are the backbone of structured data management, organising information in tables and ensuring data integrity. Introduction RDBMS is the foundation for structured data management. These databases store data in tables, which consist of rows and columns.

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Pickl AI

SEPTEMBER 20, 2024

Summary: Apache Cassandra and MongoDB are leading NoSQL databases with unique strengths. Introduction In the realm of database management systems, two prominent players have emerged in the NoSQL landscape: Apache Cassandra and MongoDB. Flexible Data Model: Supports a wide variety of data formats and allows for dynamic schema changes.

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DagsHub

NOVEMBER 11, 2024

Many find themselves swamped by the volume and complexity of unstructured data. In this article, we’ll explore how AI can transform unstructured data into actionable intelligence, empowering you to make informed decisions, enhance customer experiences, and stay ahead of the competition. What is Unstructured Data?

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Pickl AI

JULY 3, 2023

It is the process of converting raw data into relevant and practical knowledge to help evaluate the performance of businesses, discover trends, and make well-informed choices. Data gathering, data integration, data modelling, analysis of information, and data visualization are all part of intelligence for businesses.

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ODSC - Open Data Science

MARCH 23, 2023

Real-time Analytics & Built-in Machine Learning Models with a Single Database Akmal Chaudhri, Senior Technical Evangelist at SingleStore, explores the importance of delivering real-time experiences in today’s big data industry and how data models and algorithms rely on powerful and versatile data infrastructure.

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The MLOps Blog

JUNE 27, 2023

With Azure Machine Learning, data scientists can leverage pre-built models, automate machine learning tasks, and seamlessly integrate with other Azure services, making it an efficient and scalable solution for machine learning projects in the cloud. Can you see the complete model lineage with data/models/experiments used downstream?

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