ODSC - Open Data Science

JULY 19, 2023

Machine Learning Operations (MLOps) can significantly accelerate how data scientists and ML engineers meet organizational needs. 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.

Machine Learning 52

Machine Learning Data Drift Data Science Data Scientist 52

Pickl AI

JANUARY 30, 2023

Since the rise of Data Science, it has found several applications across different industrial domains. However, the programming languages that work at the core of Data Science play a significant role in it. Hence for an individual who wants to excel as a data scientist, learning Python is a must.

Python 97

Python DevOps Machine Learning Data Science 97

Pickl AI

APRIL 19, 2023

Different industries from education, healthcare to marketing, retail and ecommerce require Machine Learning Engineers. Job market will experience a rise of 13% by 2026 for ML Engineers Why is Machine Learning Important? Accordingly, an entry-level ML engineer will earn around 5.1 Consequently.

Machine Learning 52

Machine Learning ML Engineer Data Scientist ML 52

Mlearning.ai

FEBRUARY 9, 2023

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. A popular focus of a majority of Data Science courses, degrees, and online competitions is on creating a model that has the highest accuracy or best fit.

Data Scientist 52

Data Scientist Data Science ML Machine Learning 52

AWS Machine Learning Blog

FEBRUARY 13, 2024

Let’s demystify this using the following personas and a real-world analogy: Data and ML engineers (owners and producers) – They lay the groundwork by feeding data into the feature store Data scientists (consumers) – They extract and utilize this data to craft their models Data engineers serve as architects sketching the initial blueprint.

ML 130

ML Machine Learning ML Engineer Data Scientist 130

AWS Machine Learning Blog

FEBRUARY 28, 2024

medium instance with the Python 3 (Data Science) kernel. About the Authors Sanjeeb Panda is a Data and ML engineer at Amazon. Outside of his work as a Data and ML engineer at Amazon, Sanjeeb Panda is an avid foodie and music enthusiast. text_content=False, json_lines=False).load()

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Metadata LLM Generative AI NLP 129

The MLOps Blog

JUNE 27, 2023

With built-in components and integration with Google Cloud services, Vertex AI simplifies the end-to-end machine learning process, making it easier for data science teams to build and deploy models at scale. Metaflow Metaflow helps data scientists and machine learning engineers build, manage, and deploy data science projects.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

NOVEMBER 13, 2024

With the unification of SageMaker Model Cards and SageMaker Model Registry, architects, data scientists, ML engineers, or platform engineers (depending on the organization’s hierarchy) can now seamlessly register ML model versions early in the development lifecycle, including essential business details and technical metadata.

Metadata 105

Metadata ML Software Engineer Machine Learning 105

DataRobot Blog

SEPTEMBER 13, 2022

What Do Data Scientists Do? Data scientists drive business outcomes. Many implement machine learning and artificial intelligence to tackle challenges in the age of Big Data. What data scientists do is directly tied to an organization’s AI maturity level.

Data Scientist 52

Data Scientist Automation Data Ingestion ML 52

AWS Machine Learning Blog

AUGUST 31, 2023

Architecture overview The architecture is implemented as follows: Data Science Account – Data Scientists conduct their experiments in SageMaker Studio and build an MLOps setup to deploy models to staging/production environments using SageMaker Projects. Ram Vittal is a Principal ML Solutions Architect at AWS.

ML 117

ML Data Scientist Machine Learning Automation 117

Flipboard

MARCH 7, 2023

There are also limited options for ad hoc script customization by users, such as data scientists or ML engineers, due to permissions of the user profile execution role. Check that the SageMaker image selected is a Conda-supported first-party kernel image such as “Data Science.” Choose Open Launcher.

Python 123

Python Data Scientist Data Science Automation 123

AWS Machine Learning Blog

MARCH 30, 2023

He enables customers in the area of spectator sports to innovate and capitalize on their data, delivering high-quality user and fan experiences through machine learning and data science. His skills and areas of expertise include application development, data science, machine learning, and big data.

Machine Learning 88

Machine Learning Data Scientist Data Science Metadata 88

Pickl AI

JULY 14, 2023

Big Data and Deep Learning (2010s-2020s): The availability of massive amounts of data and increased computational power led to the rise of Big Data analytics. Deep Learning, a subfield of ML, gained attention with the development of deep neural networks.

Neural Network 52

Neural Network Software Engineer Artificial Intelligence Artificial Intelligence 52

AWS Machine Learning Blog

FEBRUARY 29, 2024

Configuration files (YAML and JSON) allow ML practitioners to specify undifferentiated code for orchestrating training pipelines using declarative syntax. The following are the key benefits of this solution: Automation – The entire ML workflow, from data preprocessing to model registry, is orchestrated with no manual intervention.

Automation 119

Automation Python Machine Learning ML 119

AWS Machine Learning Blog

MARCH 30, 2023

He enables customers in the area of spectator sports to innovate and capitalize on their data, delivering high-quality user and fan experiences through machine learning and data science. His skills and areas of expertise include application development, data science, machine learning, and big data.

Machine Learning 88

Machine Learning Data Scientist ML Data Science 88

AWS Machine Learning Blog

AUGUST 31, 2023

Architecture overview The architecture is implemented as follows: Data Science Account – Data Scientists conduct their experiments in SageMaker Studio and build an MLOps setup to deploy models to staging/production environments using SageMaker Projects. Ram Vittal is a Principal ML Solutions Architect at AWS.

ML 52

ML Data Scientist Machine Learning Automation 52

AWS Machine Learning Blog

OCTOBER 2, 2024

About the Authors Akarsha Sehwag is a Data Scientist and ML Engineer in AWS Professional Services with over 5 years of experience building ML based services and products. Leveraging her expertise in Computer Vision and Deep Learning, she empowers customers to harness the power of the ML in AWS cloud efficiently.

Generative AI 121

Generative AI Data Ingestion AI AI 121

AWS Machine Learning Blog

APRIL 11, 2023

These customers need to balance governance, security, and compliance against the need for machine learning (ML) teams to quickly access their data science environments in a secure manner. Rajesh Ramchander is a Senior Data & ML Engineer in Professional Services at AWS.

IDP 82

IDP Explainability Big Data DevOps 82

Pickl AI

JUNE 6, 2024

Machine Learning (ML) Machine Learning algorithms are like powerful engines, but they rely on clean fuel – clean data – to function effectively. Inaccurate data can lead to biased and unreliable models. But how can you personalize experiences and target marketing campaigns effectively if your customer data is a mess?

Machine Learning 40

Machine Learning Algorithm Business Intelligence Data Quality 40

AWS Machine Learning Blog

APRIL 19, 2023

The resulting training dataset from the processing job can be saved directly as a CSV for model training, or it can be bulk ingested into an offline feature group that can be used for other models and by other data science teams to address a wide variety of other use cases.

ML 90

ML Data Scientist Big Data Machine Learning 90

AWS Machine Learning Blog

NOVEMBER 9, 2023

Building out a machine learning operations (MLOps) platform in the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML) for organizations is essential for seamlessly bridging the gap between data science experimentation and deployment while meeting the requirements around model performance, security, and compliance.

Data Drift 125

Data Drift Auto-complete ML Automation 125

AWS Machine Learning Blog

NOVEMBER 14, 2024

Runs are executions of some piece of data science code and record metadata and generated artifacts. About the authors Ram Vittal is a Principal ML Solutions Architect at AWS. MLflow tracking allows you to programmatically track the inputs, parameters, configurations, and models of your iterations as experiments and runs.

ML 92

ML Auto-complete Auto-classification Machine Learning 92

Snorkel AI

MAY 24, 2023

The Future of Data-centric AI virtual conference will bring together a star-studded lineup of expert speakers from across the machine learning, artificial intelligence, and data science field. chief data scientist, a role he held under President Barack Obama from 2015 to 2017. Patil served as the first U.S.

Data Scientist 52

Data Scientist Machine Learning Computer Vision ML 52

Snorkel AI

MAY 24, 2023

The Future of Data-centric AI virtual conference will bring together a star-studded lineup of expert speakers from across the machine learning, artificial intelligence, and data science field. chief data scientist, a role he held under President Barack Obama from 2015 to 2017. Patil served as the first U.S.

Data Scientist 52

Data Scientist Machine Learning Computer Vision ML 52