DataRobot Blog

MAY 10, 2022

Addressing the Key Mandates of a Modern Model Risk Management Framework (MRM) When Leveraging Machine Learning . No longer is the modeler only limited to using linear models; they may now make use of varied data sources (both structured and unstructured) to build significantly higher performing models to power business processes.

Automation 64

Automation Machine Learning Data Quality Algorithm 64

AWS Machine Learning Blog

MAY 3, 2023

For any machine learning (ML) problem, the data scientist begins by working with data. 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.

Auto-classification 67

Auto-classification Auto-complete Machine Learning Metadata 67

The MLOps Blog

MAY 9, 2023

They run scripts manually to preprocess their training data, rerun the deployment scripts, manually tune their models, and spend their working hours keeping previously developed models up to date. Building end-to-end machine learning pipelines lets ML engineers build once, rerun, and reuse many times.

ML 98

ML Machine Learning Metadata Automation 98

AWS Machine Learning Blog

NOVEMBER 16, 2023

Amazon SageMaker provides purpose-built tools for machine learning operations (MLOps) to help automate and standardize processes across the ML lifecycle. For many years, Philips has been pioneering the development of data-driven algorithms to fuel its innovative solutions across the healthcare continuum.

Data Scientist 83

Data Scientist ML Data Science Automation 83

Pickl AI

JULY 23, 2023

Examples of unstructured data include text files, images, audio, and video content. While unstructured data may seem chaotic, advancements in artificial intelligence and machine learning enable us to extract valuable insights from this data type.

Data Analysis 52

Data Analysis Explainability Algorithm Natural Language Processing 52

Bugra Akyildiz

JUNE 25, 2023

This led to the development of Metis, which is a platform that enables anyone at Airbnb to search, discover, consume, and manage all the data and metadata in the company's offline warehouse. Metis has been serving critical roles across data compliance, data reliability, and data quality initiatives.

Data Quality 52

Data Quality Artificial Intelligence Artificial Intelligence Metadata 52

The MLOps Blog

APRIL 17, 2023

Building a tool for managing experiments can help your data scientists; 1 Keep track of experiments across different projects, 2 Save experiment-related metadata, 3 Reproduce and compare results over time, 4 Share results with teammates, 5 Or push experiment outputs to downstream systems.

Metadata 52

Metadata Data Scientist Explainability ML 52

Pickl AI

JANUARY 16, 2024

Join me in understanding the pivotal role of Data Analysts , where learning is not just an option but a necessity for success. Key takeaways Develop proficiency in Data Visualization, Statistical Analysis, Programming Languages (Python, R), Machine Learning, and Database Management. Value in 2022 – $18.10

Data Analysis 52

Data Analysis Data Scientist Data Science Machine Learning 52

Snorkel AI

JANUARY 31, 2023

Building a machine learning (ML) pipeline can be a challenging and time-consuming endeavor. Snorkel AI changes the paradigm with Snorkel Flow , a data-centric platform powered by state-of-the-art techniques including programmatic labeling, weak supervision, and foundation models.

Data Drift 52

Data Drift Explainability AI AI 52

Snorkel AI

JANUARY 31, 2023

Building a machine learning (ML) pipeline can be a challenging and time-consuming endeavor. Snorkel AI changes the paradigm with Snorkel Flow , a data-centric platform powered by state-of-the-art techniques including programmatic labeling, weak supervision, and foundation models.

Data Drift 52

Data Drift Explainability AI AI 52

AWS Machine Learning Blog

FEBRUARY 21, 2023

After you build, train, and evaluate your machine learning (ML) model to ensure it’s solving the intended business problem proposed, you want to deploy that model to enable decision-making in business operations. SageMaker Training jobs are then used to train an ML model on the data produced by the processing job.

ML 68

ML Automation Software Development Metadata 68

The MLOps Blog

MARCH 15, 2023

Based on the McKinsey survey , 56% of orgs today are using machine learning in at least one business function. AWS Sagemeaker is in fact a great tool for machine learning operations (MLOps) to automate and standardize processes across the ML lifecycle. This includes data quality, privacy, and compliance.

ETL 52

ETL Data Drift Machine Learning ML 52

Mlearning.ai

DECEMBER 21, 2023

Things to Keep in Mind Ensure data quality by preprocessing it before determining the optimal chunk size. Examples include removing HTML tags or eliminating specific elements that contribute noise, particularly when data is sourced from the web. Embeddings All Machine Learning/AI models work with numerical data.

Large Language Models 94

Large Language Models LLM OpenAI ChatGPT 94

AWS Machine Learning Blog

AUGUST 4, 2023

For more information about this process, refer to New — Introducing Support for Real-Time and Batch Inference in Amazon SageMaker Data Wrangler. Although we use a specific algorithm to train the model in our example, you can use any algorithm that you find appropriate for your use case.

ML 75

ML Categorization AI AI 75

Snorkel AI

AUGUST 22, 2023

We use machine learning algorithms to analyze and understand the descriptive information (e.g. Example above shows results for “modern yellow sofa” We develop machine learning algorithms to extract product tags from images which are available when suppliers upload products to our catalog.

Computer Vision 52

Computer Vision Machine Learning Data Scientist Generative AI 52

Snorkel AI

AUGUST 22, 2023

We use machine learning algorithms to analyze and understand the descriptive information (e.g. Example above shows results for “modern yellow sofa” We develop machine learning algorithms to extract product tags from images which are available when suppliers upload products to our catalog.

Computer Vision 52

Computer Vision Machine Learning Data Scientist Generative AI 52

The MLOps Blog

AUGUST 3, 2023

We want to stop the pain and suffering people feel with maintaining machine learning pipelines in production. We want to enable a team of junior data scientists to write code, take it into production, maintain it, and then when they leave, importantly, no one has nightmares about inheriting their code.

ML 52

ML Data Scientist Software Engineer Machine Learning 52