AWS Machine Learning Blog

MAY 23, 2023

Such a pipeline encompasses the stages involved in building, testing, tuning, and deploying ML models, including but not limited to data preparation, feature engineering, model training, evaluation, deployment, and monitoring. The following diagram illustrates the workflow. The following diagram illustrates this architecture.

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AWS Machine Learning Blog

MAY 3, 2023

This includes gathering, exploring, and understanding the business and technical aspects of the data, along with evaluation of any manipulations that may be needed for the model building process. One aspect of this data preparation is feature engineering.

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DataRobot Blog

MARCH 16, 2023

The DataRobot team has been working hard on new integrations that make data scientists more agile and meet the needs of enterprise IT, starting with Snowflake. We’ve tightened the loop between ML data prep , experimentation and testing all the way through to putting models into production. DataRobot Launch Event From Vision to Value.

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ODSC - Open Data Science

MAY 10, 2023

Data-centric AI, in his opinion, is based on the following principles: It’s time to focus on the data — after all the progress achieved in algorithms means it’s now time to spend more time on the data Inconsistent data labels are common since reasonable, well-trained people can see things differently.

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AWS Machine Learning Blog

OCTOBER 18, 2023

The solution focuses on the fundamental principles of developing an AI/ML application workflow of data preparation, model training, model evaluation, and model monitoring. He is passionate about helping customers to build scalable and modern data analytics solutions to gain insights from the data.

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Iguazio

DECEMBER 14, 2023

Who This Book Is For This book is for practitioners in charge of building, managing, maintaining, and operationalizing the ML process end to end: Data science / AI / ML leaders: Heads of Data Science, VPs of Advanced Analytics, AI Lead etc. Exploratory data analysis (EDA) and modeling.

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Women in Big Data

JULY 19, 2024

The Women in Big Data (WiBD) Spring Hackathon 2024, organized by WiDS and led by WiBD’s Global Hackathon Director Rupa Gangatirkar , sponsored by Gilead Sciences, offered an exciting opportunity to sharpen data science skills while addressing critical social impact challenges.

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Tableau

SEPTEMBER 23, 2021

For example, Tableau data engineers want a single source of truth to help avoid creating inconsistencies in data sets, while line-of-business users are concerned with how to access the latest data for trusted analysis when they need it most. Data modeling. Data migration . Data architecture.

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ODSC - Open Data Science

DECEMBER 16, 2024

And, for the tenth anniversary of ODSC East , we are pulling out all of the stops with new tracks, new events, and even a new location. Youll gain immediate, practical skills in Python, data preparation, machine learning modeling, and retrieval-augmented generation (RAG), all leading up to AI Agents. Find outbelow!

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Tableau

SEPTEMBER 23, 2021

For example, Tableau data engineers want a single source of truth to help avoid creating inconsistencies in data sets, while line-of-business users are concerned with how to access the latest data for trusted analysis when they need it most. Data modeling. Data migration . Data architecture.

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DataRobot Blog

OCTOBER 3, 2017

Enterprise data architects, data engineers, and business leaders from around the globe gathered in New York last week for the 3-day Strata Data Conference , which featured new technologies, innovations, and many collaborative ideas.

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Mlearning.ai

APRIL 6, 2023

So we have to create an event rule on AWS EventBridge that monitors the SageMaker batch inference job and will push the message to the SQS after completing the batch inference job. Check Tweets Batch Inference Job Status: Create an SQS listener that reads a message from the queue when the event rule publishes it.

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ODSC - Open Data Science

JANUARY 29, 2024

Using skills such as statistical analysis and data visualization techniques, prompt engineers can assess the effectiveness of different prompts and understand patterns in the responses. For prompt engineers, it can be used for the deployment and orchestration of LLM applications. Interested in attending an ODSC event?

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Iguazio

FEBRUARY 8, 2024

Data engineers, data scientists and other data professional leaders have been racing to implement gen AI into their engineering efforts. MLRun automates various stages of the ML lifecycle, such as data preparation, model training and deployment. LLMOps is MLOps for LLMs.

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The MLOps Blog

JUNE 27, 2023

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. This provides end-to-end support for data engineering and MLOps workflows.

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Pickl AI

SEPTEMBER 5, 2024

Data Preparation: Cleaning, transforming, and preparing data for analysis and modelling. Collaborating with Teams: Working with data engineers, analysts, and stakeholders to ensure data solutions meet business needs.

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AWS Machine Learning Blog

JANUARY 26, 2024

Plan for rollback and recovery from production security events and service disruptions such as prompt injection, training data poisoning, model denial of service, and model theft early on, and define the mitigations you will use as you define application requirements.

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Kaggle

JULY 29, 2020

In August 2019, Data Works was acquired and Dave worked to ensure a successful transition. David: My technical background is in ETL, data extraction, data engineering and data analytics. Do you have any advice for those just getting started in data science? David, what can you tell us about your background?

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