Marktechpost

JANUARY 31, 2024

Data scientists and ML engineers often need help to build full-stack applications. These professionals typically have a firm grasp of data and AI algorithms. It is a Python-based framework for data scientists and machine learning engineers. This is where Taipy comes into play.

Data Scientist 133

Data Scientist Machine Learning Python ML Engineer 133

AWS Machine Learning Blog

OCTOBER 22, 2024

Amazon SageMaker is a cloud-based machine learning (ML) platform within the AWS ecosystem that offers developers a seamless and convenient way to build, train, and deploy ML models. The solution illustrated in this post focuses on the new SageMaker Studio experience, particularly private JupyterLab and Code Editor spaces.

ML Engineer 108

ML Engineer Data Scientist Machine Learning ML 108

AI News

JULY 28, 2023

According to a recent report by Harnham , a leading data and analytics recruitment agency in the UK, the demand for ML engineering roles has been steadily rising over the past few years. Harnham’s report provides comprehensive insights into the salaries and day rates of various data science roles across the UK.

ML 246

ML Data Science ML Engineer Big Data 246

Unite.AI

JANUARY 27, 2025

End users should also seek companies that can help with this testing as often an ML Engineer can help with deployment vs. the Data Scientist that created the model. Quite often deployment of a large model is too expensive to make it practical for use.

Deep Learning 162

Deep Learning Data Quality ML Engineer Data Scientist 162

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.

Data Science 70

Data Science Data Scientist Data Ingestion DevOps 70

Towards AI

AUGUST 7, 2024

From Solo Notebooks to Collaborative Powerhouse: VS Code Extensions for Data Science and ML Teams Photo by Parabol | The Agile Meeting Toolbox on Unsplash In this article, we will explore the essential VS Code extensions that enhance productivity and collaboration for data scientists and machine learning (ML) engineers.

Data Science 116

Data Science ML ML Engineer Data Scientist 116

Unite.AI

FEBRUARY 12, 2025

The AI/ML engine built into MachineMetrics analyzes this machine data to detect anomalies and patterns that might indicate emerging problems. Continuous Anomaly Detection: Continuously monitors data streams and uses AI to detect anomalies or deviations, instantly alerting teams to potential problems.

AI Tools 260

AI Tools Machine Learning Auto-complete AI 260

Eugene Yan

JANUARY 16, 2019

What's the difference between a data scientist, data engineer, and ML engineer? A panel at Google.

ML Engineer 130

ML Engineer Data Scientist ML 130

AWS Machine Learning Blog

FEBRUARY 19, 2025

In this example, the ML engineering team is borrowing 5 GPUs for their training task With SageMaker HyperPod, you can additionally set up observability tools of your choice. Data scientist experience Data scientists are the second persona interacting with SageMaker HyperPod clusters. HyperPod CLI v2.0.0

Data Scientist 72

Data Scientist Data Science ML Engineer Generative AI 72

IBM Journey to AI blog

AUGUST 11, 2023

Because the machine learning lifecycle has many complex components that reach across multiple teams, it requires close-knit collaboration to ensure that hand-offs occur efficiently, from data preparation and model training to model deployment and monitoring. How to use ML to automate the refining process into a cyclical ML process.

Data Science 170

Data Science DevOps Machine Learning Data Scientist 170

IBM Journey to AI blog

AUGUST 12, 2024

It helps companies streamline and automate the end-to-end ML lifecycle, which includes data collection, model creation (built on data sources from the software development lifecycle), model deployment, model orchestration, health monitoring and data governance processes.

Big Data 266

Big Data DevOps Automation Machine Learning 266

AWS Machine Learning Blog

JANUARY 23, 2025

The solution described in this post is geared towards machine learning (ML) engineers and platform teams who are often responsible for managing and standardizing custom environments at scale across an organization.

Automation 104

Automation DevOps Machine Learning ML 104

Towards AI

MARCH 14, 2024

So, before we look at how to learn data science, we need to know: what really is a data scientist? I mean, ML engineers often spend most of their time handling and understanding data. So, how is a data scientist different from an ML engineer?

Data Science 105

Data Science ML Engineer Data Scientist ML 105

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. Direct internet access is disabled within their domain.

ML 149

ML DevOps Data Scientist ML Engineer 149

TheSequence

MARCH 8, 2024

VEW SPEAKER LINEUP Here’s a sneak peek of the agenda: LangChain Keynote: Hear from Lance Martin, an ML leader at LangChain, a leading orchestration framework for large language models (LLMs). Dive deep into these topics with our expert speakers and gain actionable insights for mastering AI and ML.

ML Engineer 52

ML Engineer ML Large Language Models Data Scientist 52

AWS Machine Learning Blog

DECEMBER 12, 2024

The new SDK is designed with a tiered user experience in mind, where the new lower-level SDK ( SageMaker Core ) provides access to full breadth of SageMaker features and configurations, allowing for greater flexibility and control for ML engineers.

ML 87

ML Python Data Scientist Natural Language Processing 87

ODSC - Open Data Science

MARCH 10, 2025

Training Sessions Bayesian Analysis of Survey Data: Practical Modeling withPyMC Allen Downey, PhD, Principal Data Scientist at PyMCLabs Alexander Fengler, Postdoctoral Researcher at Brown University Bayesian methods offer a flexible and powerful approach to regression modeling, and PyMC is the go-to library for Bayesian inference in Python.

Data Scientist 52

Data Scientist Data Science LLM Machine Learning 52

TheSequence

NOVEMBER 3, 2023

Manager, ML Engineering at HelloFresh “Fireside Chat: LLMs, Real Time & Other Trends in the Production ML Space,” with Ali Ghodsi, CEO & Co-founder at Databricks , and Mike Del Balso, CEO & Co-founder at Tecton “Evolution of the Ads Ranking System at Pinterest,” by Aayush Mudgal, Sr.

ML Engineer 52

ML Engineer ML Software Engineer Data Scientist 52

Unite.AI

JUNE 29, 2023

The Vertex AI platform has gained growing popularity among clients as it accelerates ML development, slashing production time by up to 80% compared to alternative methods. It offers an extensive suite of ML Ops capabilities, enabling ML engineers, data scientists, and developers to contribute efficiently.

Machine Learning 262

Machine Learning ML AI AI 262

AWS Machine Learning Blog

DECEMBER 9, 2024

In the initial stages of an ML project, data scientists collaborate closely, sharing experimental results to address business challenges. MLflow , a popular open-source tool, helps data scientists organize, track, and analyze ML and generative AI experiments, making it easier to reproduce and compare results.

ML 92

ML Data Scientist Machine Learning Software Engineer 92

AWS Machine Learning Blog

JULY 8, 2024

TWCo data scientists and ML engineers took advantage of automation, detailed experiment tracking, integrated training, and deployment pipelines to help scale MLOps effectively. ML model experimentation is one of the sub-components of the MLOps architecture.

Data Scientist 114

Data Scientist ML Engineer Machine Learning Data Science 114

AWS Machine Learning Blog

OCTOBER 20, 2023

The ML team lead federates via IAM Identity Center, uses Service Catalog products, and provisions resources in the ML team’s development environment. Data scientists from ML teams across different business units federate into their team’s development environment to build the model pipeline.

ML 126

ML Data Scientist ML Engineer Data Science 126

Marktechpost

OCTOBER 10, 2024

Data Analysis : Applying statistical methods to discover trends. Data Visualization : Presenting findings via charts and graphs. Predictive Modeling : Using data to predict future outcomes. Data scientists need to be skilled in programming, statistics, and domain knowledge. What is Machine Learning?

Data Science 106

Data Science Machine Learning Data Scientist ML Engineer 106

AWS Machine Learning Blog

OCTOBER 16, 2024

Amazon SageMaker supports geospatial machine learning (ML) capabilities, allowing data scientists and ML engineers to build, train, and deploy ML models using geospatial data. These geospatial capabilities open up a new world of possibilities for environmental monitoring.

Machine Learning 107

Machine Learning ML Data Scientist Robotics 107

Mlearning.ai

FEBRUARY 9, 2023

Working as a Data Scientist — Expectation versus Reality! 11 key differences in 2023 Photo by Jan Tinneberg on Unsplash Working in Data Science and Machine Learning (ML) professions can be a lot different from the expectation of it. You could be working entirely on data analytics under a Data Scientist job title.

Data Scientist 52

Data Scientist Data Science ML Machine Learning 52

AWS Machine Learning Blog

DECEMBER 19, 2023

Artificial intelligence (AI) and machine learning (ML) are becoming an integral part of systems and processes, enabling decisions in real time, thereby driving top and bottom-line improvements across organizations. However, putting an ML model into production at scale is challenging and requires a set of best practices.

Machine Learning 127

Machine Learning ML Engineer DevOps ML 127

AWS Machine Learning Blog

FEBRUARY 11, 2025

Clean up To clean up the model and endpoint, use the following code: predictor.delete_model() predictor.delete_endpoint() Conclusion In this post, we explored how SageMaker JumpStart empowers data scientists and ML engineers to discover, access, and run a wide range of pre-trained FMs for inference, including the Falcon 3 family of models.

ML 79

ML Machine Learning Python Computer Vision 79

AWS Machine Learning Blog

OCTOBER 28, 2024

You can use this framework as a starting point to monitor your custom metrics or handle other unique requirements for model quality monitoring in your AI/ML applications. Data Scientist at AWS, bringing a breadth of data science, ML engineering, MLOps, and AI/ML architecting to help businesses create scalable solutions on AWS.

ML 104

ML Metadata Data Scientist DevOps 104

DataRobot Blog

SEPTEMBER 13, 2022

According to IDC , 83% of CEOs want their organizations to be more data-driven. Data scientists could be your key to unlocking the potential of the Information Revolution—but what do data scientists do? What Do Data Scientists Do? Data scientists drive business outcomes.

Data Scientist 52

Data Scientist Automation ML Machine Learning 52

O'Reilly Media

JANUARY 17, 2023

Because if companies use code to automate business rules, they use ML/AI to automate decisions. Given that, what would you say is the job of a data scientist (or ML engineer, or any other such title)? But first, let’s talk about the typical ML workflow. I’ll share my answer in a bit.

Automation 145

Automation Robotics Data Scientist ML 145

ODSC - Open Data Science

FEBRUARY 2, 2023

The role of a data scientist is in demand and 2023 will be no exception. To get a better grip on those changes we reviewed over 25,000 data scientist job descriptions from that past year to find out what employers are looking for in 2023. Data Science Of course, a data scientist should know data science!

Data Science 98

Data Science Data Scientist Big Data Machine Learning 98

Marktechpost

JUNE 19, 2024

Generative AI Fundamentals Specialization This specialization offers a comprehensive introduction to generative AI, covering models like GPT and DALL-E, prompt engineering, and ethical considerations. It includes five self-paced courses with hands-on labs and projects using tools like ChatGPT, Stable Diffusion, and IBM Watsonx.ai.

Artificial Intelligence 121

Artificial Intelligence Artificial Intelligence Prompt Engineer Prompt Engineering 121

Marktechpost

MAY 30, 2024

Introduction to AI and Machine Learning on Google Cloud This course introduces Google Cloud’s AI and ML offerings for predictive and generative projects, covering technologies, products, and tools across the data-to-AI lifecycle.

Artificial Intelligence 130

Artificial Intelligence Artificial Intelligence BERT Computer Vision 130

AWS Machine Learning Blog

JANUARY 28, 2025

FMEval is an open source LLM evaluation library, designed to provide data scientists and machine learning (ML) engineers with a code-first experience to evaluate LLMs for various aspects, including accuracy, toxicity, fairness, robustness, and efficiency.

LLM 100

LLM Large Language Models ML Algorithm 100

O'Reilly Media

OCTOBER 19, 2021

They are often built by data scientists who are not software engineers or computer science majors by training. Python written in Jupyter notebooks following the tradition of data-centric programming is very different from Python used to implement a scalable web server. Data Science Layers. Software Architecture.

DevOps 145

DevOps Software Engineer Data Scientist ML 145

O'Reilly Media

MARCH 18, 2025

You can’t just cram a bunch of data scientists into an office and cross your fingers that everything works out. Bringing AI into a company means you have new roles to fill (data scientist, ML engineer) as well as new knowledge to backfill in existing roles (product, ops).

Software Development 52

Software Development Python Data Scientist AI 52

Marktechpost

DECEMBER 1, 2024

Simplified Synthetic Data Generation Designed to generate synthetic datasets using either local large language models (LLMs) or hosted models (OpenAI, Anthropic, Google Gemini, etc.), Promptwright makes synthetic data generation more accessible and flexible for developers and data scientists.

Python 88

Python LLM Data Scarcity Data Scientist 88