IBM Journey to AI blog

JANUARY 10, 2024

AI can also work from deep learning algorithms, a subset of ML that uses multi-layered artificial neural networks (ANNs)—hence the “deep” descriptor—to model high-level abstractions within big data infrastructures. This process can prove unmanageable, if not impossible, for many organizations.

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Unite.AI

FEBRUARY 21, 2024

Airflow provides the workflow management capabilities that are integral to modern cloud-native data platforms. It automates the execution of jobs, coordinates dependencies between tasks, and gives organizations a central point of control for monitoring and managing workflows.

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IBM Journey to AI blog

MAY 21, 2024

At the time, Sevilla FC could efficiently access and use quantitative player data in a matter of seconds, but the process of extracting qualitative information from the database was much slower in comparison. In the case of Sevilla FC, using big data to recruit players had the potential to change the core business.

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ODSC - Open Data Science

OCTOBER 9, 2024

By automating repetitive tasks and generating boilerplate code, these tools free up time for engineers to focus on more complex, creative aspects of software development. Well, it is offering a way to automate the time-consuming process of writing and running tests. Just keep in mind, that this shouldn’t replace the human element.

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AWS Machine Learning Blog

DECEMBER 18, 2023

In this post, we will explore the potential of using MongoDB’s time series data and SageMaker Canvas as a comprehensive solution. MongoDB Atlas MongoDB Atlas is a fully managed developer data platform that simplifies the deployment and scaling of MongoDB databases in the cloud.

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Marktechpost

JUNE 5, 2024

You may use OpenRefine for more than just data cleaning; it can also help you find mistakes and outliers that could compromise your data’s quality. Apache Griffin Apache Griffin is an open-source data quality tool that aims to enhance big data processes. It has a quick and clear grasp of data quality issues.

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AWS Machine Learning Blog

MAY 15, 2023

We outline how we built an automated demand forecasting pipeline using Forecast and orchestrated by AWS Step Functions to predict daily demand for SKUs. Forecast automates much of the time-series forecasting process, enabling you to focus on preparing your datasets and interpreting your predictions.

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AWS Machine Learning Blog

DECEMBER 7, 2023

Additionally, for insights on constructing automated workflows and crafting machine learning pipelines, you can explore AWS Step Functions for comprehensive guidance. He worked at Turkcell, mainly focused on time series forecasting, data visualization, and network automation.

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AWS Machine Learning Blog

OCTOBER 20, 2023

A framework for vending new accounts is also covered, which uses automation for baselining new accounts when they are provisioned. You can start small with one account for your data platform foundations for a proof of concept or a few small workloads.

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AWS Machine Learning Blog

FEBRUARY 13, 2024

The implementation of an AI-powered automated self-checkout system delivers an improved retail customer experience through innovation, while eliminating human errors in the checkout process. Integrating FSx for Lustre enables fast parallel data access for efficient model retraining with hundreds of new SKUs monthly.

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Flipboard

NOVEMBER 24, 2023

This offering enables BMW ML engineers to perform code-centric data analytics and ML, increases developer productivity by providing self-service capability and infrastructure automation, and tightly integrates with BMW’s centralized IT tooling landscape. A data scientist team orders a new JuMa workspace in BMW’s Catalog.

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Marktechpost

JULY 17, 2023

Data gathering, pre-processing, modeling, and deployment are all steps in the iterative process of predictive analytics that results in output. We can automate the procedure to deliver forecasts based on new data continuously fed throughout time. This tool’s user-friendly UI consistently receives acclaim from users.

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Artificial Corner

JUNE 6, 2023

Timeline of data engineering — Created by the author using canva In this post, I will cover everything from the early days of data storage and relational databases to the emergence of big data, NoSQL databases, and distributed computing frameworks. MongoDB, developed by MongoDB Inc.,

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Data Mining Big Data ETL Machine Learning 52

IBM Journey to AI blog

JULY 7, 2023

Use dedicated data security software. An integrated data protection system can protect your assets by monitoring them, automating access control, setting up notifications, and auditing your password management. Secure databases in the physical data center, big data platforms and the cloud.

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Marktechpost

JULY 18, 2023

The entire ETL procedure is automated using an ETL tool. ETL solutions employ several data management strategies to automate the extraction, transformation, and loading (ETL) process, reducing errors and speeding up data integration. Large-scale businesses and Big Data firms are its primary target market.

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Pickl AI

OCTOBER 6, 2024

A successful load ensures Analysts and decision-makers access to up-to-date, clean data. Common ETL Tools and Technologies Several tools facilitate the ETL process, helping organisations automate and streamline data integration. Apache NiFi : An open-source tool designed for data flow automation and ETL processes.

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The MLOps Blog

MARCH 15, 2023

As the volume of data keeps increasing at an accelerated rate, these data tasks become arduous in no time leading to an extensive need for automation. This is what data processing pipelines do for you. Let’s understand how the other aspects of a data pipeline help the organization achieve its various objectives.

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ODSC - Open Data Science

OCTOBER 20, 2023

HPCC Systems — The Kit and Kaboodle for Big Data and Data Science Bob Foreman | Software Engineering Lead | LexisNexis/HPCC Join this session to learn how ECL can help you create powerful data queries through a comprehensive and dedicated data lake platform.

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John Snow Labs

AUGUST 7, 2024

For example, McKinsey points out that GenAI can automate the summarization of vast amounts of data from patient logs, which is a time-consuming task, thus freeing up healthcare professionals to focus on more complex patient needs.

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ODSC - Open Data Science

JULY 19, 2023

A well-implemented MLOps process not only expedites the transition from testing to production but also offers ownership, lineage, and historical data about ML artifacts used within the team. For the customer, this helps them reduce the time it takes to bootstrap a new data science project and get it to production.

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Pickl AI

JUNE 12, 2023

Disadvantages of Tableau for Data Science However, apart from the advantages, Tableau for Data Science also has its own disadvantages. These can be explained as follows: Tableau doesn’t have the feature of integration and while Data Scientists make use of automation and integrations.

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Flipboard

MARCH 22, 2023

In this post, we show how to configure a new OAuth-based authentication feature for using Snowflake in Amazon SageMaker Data Wrangler. Snowflake is a cloud data platform that provides data solutions for data warehousing to data science. Bosco Albuquerque is a Sr.

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IDP Data Scientist Categorization Data Quality 123

John Snow Labs

FEBRUARY 29, 2024

For example, McKinsey points out that Gen AI can automate the summarization of vast amounts of data from patient logs, which is a time-consuming task, thus freeing up healthcare professionals to focus on more complex patient needs​​.

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AWS Machine Learning Blog

AUGUST 3, 2023

Use cases range from self-driving cars, content moderation on social media platforms, cancer detection, and automated defect detection. Aamna Najmi is a Data Scientist with AWS Professional Services. She has experience in working on data platform and AI/ML projects in the healthcare and life sciences vertical.

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AWS Machine Learning Blog

SEPTEMBER 6, 2024

Experimenting with LLMs to automate fact generation from QA ground truth using LLMs can help. Automate, but verify, with LLMs – Use LLMs to generate initial ground truth answers and facts, with a human review and curation to align with the desired assistant output standards.

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IBM Journey to AI blog

JUNE 15, 2023

To help organizations scale AI workloads, we recently announced IBM watsonx.data , a data store built on an open data lakehouse architecture and part of the watsonx AI and data platform. Let’s dive into the analytics landscape and what makes watsonx.data unique.

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Marktechpost

NOVEMBER 1, 2024

From data preparation to model deployment, it provides a comprehensive solution. RapidMiner’s versatility for a wide range of data types includes the ability to analyze text, pictures, and audio. Yellowfin’s analytics platform and first-rate customer service allow users to gain insights quickly and effectively.

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TransOrg Analytics

SEPTEMBER 24, 2024

Our cloud data engineering services are designed to transform your business by creating robust and scalable data foundations across any scale. We provide comprehensive solutions to assess, architect, build, deploy, and automate your data engineering landscape on the leading cloud platforms.

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Pickl AI

JUNE 11, 2024

In-Memory Computing This technology allows for storing and processing data in RAM for faster query response times, enabling real-time analytics. Big Data Integration Data warehouses are increasingly incorporating big data technologies to handle vast volumes of data from diverse sources.

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IBM Journey to AI blog

AUGUST 3, 2023

The risks include non-compliance to regulatory requirements and can lead to excessive hoarding of sensitive data when it’s not necessary. It’s both a data security and privacy issue.

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