AWS Machine Learning Blog

FEBRUARY 21, 2025

This also led to a backlog of data that needed to be ingested. Steep learning curve for data scientists: Many of Rockets data scientists did not have experience with Spark, which had a more nuanced programming model compared to other popular ML solutions like scikit-learn.

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Data Science Data Scientist Data Ingestion DevOps 72

IBM Journey to AI blog

OCTOBER 4, 2023

Enter IBM watsonx.data , a fit-for-purpose data store built on an open data lakehouse, to scale AI workloads, for all your data, anywhere. Watsonx.data is part of IBM’s AI and data platform, watsonx, that empowers enterprises to scale and accelerate the impact of AI across the business.

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Metadata AI Strategy Data Scientist Big Data 238

IBM Journey to AI blog

SEPTEMBER 20, 2023

While that can mean hiring new talent like data scientists and software programmers, it should also mean providing existing workers with the training they need to manage AI-related projects. At all levels of governments, from national entities to local governments, public employees must be ready for this new AI era.

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AWS Machine Learning Blog

APRIL 1, 2025

Insagic is a next-generation insights and advisory business that combines data, design, and dialogues to deliver actionable insights and transformational intelligence for healthcare marketers. It uses expertise from data scientists, behavior scientists, and strategists to drive better outcomes in the healthcare industry.

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LLM Data Scientist Data Science Generative AI 108

IBM Journey to AI blog

DECEMBER 20, 2023

For instance, if data scientists were building a model for tornado forecasting, the input variables might include date, location, temperature, wind flow patterns and more, and the output would be the actual tornado activity recorded for those days. the target or outcome variable is known).

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IBM Journey to AI blog

AUGUST 1, 2023

Instead of spending time and effort on training a model from scratch, data scientists can use pretrained foundation models as starting points to create or customize generative AI models for a specific use case. The platform comprises three powerful products: The watsonx.ai

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IBM Journey to AI blog

JULY 27, 2023

Precisely conducted a study that found that within enterprises, data scientists spend 80% of their time cleaning, integrating and preparing data , dealing with many formats, including documents, images, and videos. Overall placing emphasis on establishing a trusted and integrated data platform for AI.

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Generative AI Chatbots Data Scientist AI 173

Pickl AI

APRIL 14, 2023

Falling into the wrong hands can lead to the illicit use of this data. Hence, adopting a Data Platform that assures complete data security and governance for an organization becomes paramount. In this blog, we are going to discuss more on What are Data platforms & Data Governance.

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Data Platform Data Integration Data Ingestion Automation 52

IBM Journey to AI blog

AUGUST 2, 2023

Wf360 delivers one integrated HR profile spanning career, skills, performance, learning, and compensation, incorporating both daily snapshots and historical data.

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Data Quality Data Scientist Automation Data Platform 184

ODSC - Open Data Science

MARCH 18, 2025

Allen Downey, PhD, Principal Data Scientist at PyMCLabs Allen is the author of several booksincluding Think Python, Think Bayes, and Probably Overthinking Itand a blog about data science and Bayesian statistics. This years event is no different, and heres a rundown of 15 fan-favorite speakers who are returning onceagain.

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Data Science Machine Learning Software Engineer Data Scientist 64

IBM Journey to AI blog

MAY 21, 2024

But when it came to the massive amount of data collected by scouters, the department knew it had a challenge that would take a reliable partner. Initially, the department consulted with data scientists at the University of Sevilla to develop models to organize all their data.

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NLP Natural Language Processing Explainability Data Scientist 211

AWS Machine Learning Blog

OCTOBER 20, 2023

Data scientists from ML teams across different business units federate into their team’s development environment to build the model pipeline. Data scientists search and pull features from the central feature store catalog, build models through experiments, and select the best model for promotion.

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ML Data Scientist ML Engineer Data Science 127

IBM Journey to AI blog

JUNE 12, 2023

A long-standing partnership between IBM Human Resources and IBM Global Chief Data Office (GCDO) aided in the recent creation of Workforce 360 (Wf360), a workforce planning solution using IBM’s Cognitive Enterprise Data Platform (CEDP).

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IBM Journey to AI blog

OCTOBER 20, 2023

By exploring data from different perspectives with visualizations, you can identify patterns, connections, insights and relationships within that data and quickly understand large amounts of information. AutoAI automates data preparation, model development, feature engineering and hyperparameter optimization.

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IBM Journey to AI blog

AUGUST 22, 2024

For more than three decades, teams of developers and data scientists from IBM Consulting® have collaborated with the United States Tennis Association (USTA) to provide an engaging digital experience for US Open tennis fans. Next, the Match Reports are created.

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Generative AI Automation Data Scientist Data Platform 243

Flipboard

NOVEMBER 24, 2023

In an increasingly digital and rapidly changing world, BMW Group’s business and product development strategies rely heavily on data-driven decision-making. With that, the need for data scientists and machine learning (ML) engineers has grown significantly. A data scientist team orders a new JuMa workspace in BMW’s Catalog.

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ML DevOps Data Scientist ML Engineer 151

AWS Machine Learning Blog

FEBRUARY 27, 2024

Axfood has a structure with multiple decentralized data science teams with different areas of responsibility. Together with a central data platform team, the data science teams bring innovation and digital transformation through AI and ML solutions to the organization.

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Machine Learning DevOps Data Scientist Data Quality 135

IBM Journey to AI blog

JULY 17, 2023

With the recent launch of watsonx, IBM’s next-generation AI and data platform, AI is being taken to the next level with three powerful components: watsonx.ai, watsonx.data and watsonx.governance. Watsonx.ai is a studio to train, validate, tune and deploy machine learning (ML) and foundation models for Generative AI.

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IBM Journey to AI blog

JULY 17, 2023

Within watsonx.ai, users can take advantage of open-source frameworks like PyTorch, TensorFlow and scikit-learn alongside IBM’s entire machine learning and data science toolkit and its ecosystem tools for code-based and visual data science capabilities.

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AWS Machine Learning Blog

AUGUST 4, 2023

As a result, businesses can accelerate time to market while maintaining data integrity and security, and reduce the operational burden of moving data from one location to another. With Einstein Studio, a gateway to AI tools on the data platform, admins and data scientists can effortlessly create models with a few clicks or using code.

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ODSC - Open Data Science

DECEMBER 7, 2023

How to Add Domain-Specific Knowledge to an LLM Based on Your Data In this article, we will explore one of several strategies and techniques to infuse domain knowledge into LLMs, allowing them to perform at their best within specific professional contexts by adding chunks of documentation into an LLM as context when injecting the query.

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Data Scientist Explainable AI Data Science Python 98

IBM Journey to AI blog

SEPTEMBER 25, 2023

Uber’s prowess as a transportation, logistics and analytics company hinges on their ability to leverage data effectively. The pursuit of hyperscale analytics The scale of Uber’s analytical endeavor requires careful selection of data platforms with high regard for limitless analytical processing.

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Automation ETL Data Scientist Data Science 256

IBM Journey to AI blog

AUGUST 4, 2023

When effectively implemented, a data democracy simplifies the data stack, eliminates data gatekeepers, and makes the company’s comprehensive data platform easily accessible by different teams via a user-friendly dashboard. Beyond the technical aspects, the goals are far loftier.

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Machine Learning Metadata Automation AI 183

IBM Journey to AI blog

SEPTEMBER 20, 2023

These include data ingestion, data selection, data pre-processing, FM pre-training, model tuning to one or more downstream tasks, inference serving, and data and AI model governance and lifecycle management—all of which can be described as FMOps. IBM watsonx consists of the following: IBM watsonx.ai

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Large Language Models DevOps Data Science AI Modeling 238

AWS Machine Learning Blog

SEPTEMBER 18, 2023

SageMaker geospatial capabilities make it easy for data scientists and machine learning (ML) engineers to build, train, and deploy models using geospatial data. UHeat uses a combination of satellite imagery and open-source climate data to perform the analysis. This now takes a matter of hours with SageMaker.

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Data Scientist ML Machine Learning ML Engineer 119

Unite.AI

FEBRUARY 21, 2024

Airflow provides the workflow management capabilities that are integral to modern cloud-native data platforms. Data platform architects leverage Airflow to automate the movement and processing of data through and across diverse systems, managing complex data flows and providing flexible scheduling, monitoring, and alerting.

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LLM Data Platform Software Engineer Chatbots 147

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. Shut down the Studio app and relaunch for the changes to take effect.

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IDP Data Scientist Categorization Data Quality 123

AWS Machine Learning Blog

MARCH 11, 2024

The new VistaPrint personalized product recommendation system Figure 1 As seen in Figure 1, the steps in how VistaPrint provides personalized product recommendations with their new cloud-native architecture are: Aggregate historical data in a data warehouse. Transform the data to create Amazon Personalize training data.

Machine Learning 120

Machine Learning Data Platform Software Engineer Data Scientist 120

The MLOps Blog

MARCH 21, 2023

From gathering and processing data to building models through experiments, deploying the best ones, and managing them at scale for continuous value in production—it’s a lot. As the number of ML-powered apps and services grows, it gets overwhelming for data scientists and ML engineers to build and deploy models at scale.

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69

deepsense.ai

MAY 8, 2023

SQLDay, one of the biggest Microsoft Data Platform conferences in Europe, is set to host an insightful presentation on GPT in data analysis by Maksymilian Operlejn, Data Scientist at deepsense.ai. The presentation entitled “GPT in data analysis – will AI replace us?”

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Data Analysis Data Scientist Big Data Data Platform 52

AWS Machine Learning Blog

DECEMBER 7, 2023

She then joined Getir in 2022 as a data scientist and has worked on Recommendation Engine projects, Mathematical Programming for Workforce Planning. Emre Uzel received his Master’s Degree in Data Science from Koç University. She worked as a researcher at TUBITAK, focusing on time series forecasting & visualization.

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Convolutional Neural Networks Algorithm Neural Network Data Science 125

Marktechpost

JULY 17, 2023

Best predictive analytics tools and platforms H2O Driverless AI H2O, a relative newcomer to predictive analytics, became well-known thanks to a well-liked open source solution. IBM merged the critical capabilities of the vendor into its more contemporary Watson Studio running on the IBM Cloud Pak for Data platform as it continues to innovate.

Machine Learning 98

Machine Learning Data Mining Data Scientist Data Science 98

Pickl AI

JUNE 12, 2023

With the help of Tableau, organisations have been able to mine and gather actionable insights from granular sources of data. Tableau can help Data Scientists generate graphs, charts, maps and data-driven stories, etc for purpose of visualisation and analysing data.

Data Science 52

Data Science Data Scientist Data Analysis Machine Learning 52

AWS Machine Learning Blog

OCTOBER 3, 2024

This approach led to data scientists spending more than 50% of their time on operational tasks, leaving little room for innovation, and posed challenges in monitoring model performance in production. This feature integrates with Amazon SageMaker Experiments to provide data scientists with insights into the tuning process.

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DevOps Data Science Data Scientist ML 90

Mlearning.ai

MARCH 15, 2023

Data professionals are in high demand all over the globe due to the rise in big data. The roles of data scientists and data analysts cannot be over-emphasized as they are needed to support decision-making. This article will serve as an ultimate guide to choosing between Data Science and Data Analytics.

Data Science 52

Data Science Data Scientist Big Data Machine Learning 52

IBM Journey to AI blog

APRIL 18, 2024

Building an in-house team with AI, deep learning , machine learning (ML) and data science skills is a strategic move. Most importantly, no matter the strength of AI (weak or strong), data scientists, AI engineers, computer scientists and ML specialists are essential for developing and deploying these systems.

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AWS Machine Learning Blog

MAY 15, 2023

Mutlu Polatcan is a Staff Data Engineer at Getir, specializing in designing and building cloud-native data platforms. She worked as a data scientist at Arcelik, focusing on spare-part recommendation models and age, gender, emotion analysis from speech data.

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