Towards AI

JULY 23, 2024

Matt Holden noted on x/twitter that in the early days of cloud storage — in its first decade (2006–2016), Amazon S3 cost per GB of storage dropped 86% (or ~97%, including Glacier). The speed of AI cost reduction is dramatically faster, potentially enabling much more rapid adoption relative to cloud computing.

Cloud Computing 105

Cloud Computing AI AI Data Preparation 105

AWS Machine Learning Blog

DECEMBER 18, 2024

This strategic decision was driven by several factors: Efficient data preparation Building a high-quality pre-training dataset is a complex task, involving assembling and preprocessing text data from various sources, including web sources and partner companies. The team opted for fine-tuning on AWS.

Clustering 102

Clustering AWS AI AI 102

AWS Machine Learning Blog

DECEMBER 13, 2023

We create an automated model build pipeline that includes steps for data preparation, model training, model evaluation, and registration of the trained model in the SageMaker Model Registry. Pooya Vahidi is a Senior Solutions Architect at AWS, passionate about computer science, artificial intelligence, and cloud computing.

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AWS ML ML Data Preparation 127

ODSC - Open Data Science

MARCH 18, 2025

With over 30 years in techincluding key roles at Hugging Face, AWS, and as a startup CTOhe brings unparalleled expertise in cloud computing and machine learning. This session covers key CV concepts, real-world use cases, and step-by-step guidance on data preparation, model selection, and fine-tuning.

Data Science 64

Data Science Machine Learning Machine Learning Data Scientist 64

ODSC - Open Data Science

NOVEMBER 19, 2024

Dimensional Data Modeling in the Modern Era by Dustin Dorsey Slides Dustin Dorsey’s AI slides explored the evolution of dimensional data modeling, a staple in data warehousing and business intelligence. Despite the rise of big data technologies and cloud computing, the principles of dimensional modeling remain relevant.

Deep Learning 52

Deep Learning Deep Learning Data Science AI 52

Pickl AI

NOVEMBER 28, 2024

Familiarity with cloud computing tools supports scalable model deployment. Data Transformation Transforming data prepares it for Machine Learning models. Encoding categorical variables converts non-numeric data into a usable format for ML models, often using techniques like one-hot encoding.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

DECEMBER 4, 2024

Currently, organisations across sectors are leveraging Data Science to improve customer experiences, streamline operations, and drive strategic initiatives. A key aspect of this evolution is the increased adoption of cloud computing, which allows businesses to store and process vast amounts of data efficiently.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

ODSC - Open Data Science

OCTOBER 9, 2023

BPCS’s deep understanding of Databricks can help organizations of all sizes get the most out of the platform, with services spanning data migration, engineering, science, ML, and cloud optimization. HPCC is a high-performance computing platform that helps organizations process and analyze large amounts of data.

Machine Learning 52

Machine Learning Machine Learning Data Science AI 52

AWS Machine Learning Blog

NOVEMBER 16, 2023

Access to AWS environments SageMaker and associated AI/ML services are accessed with security guardrails for data preparation, model development, training, annotation, and deployment. Irina has a strong technical background in machine learning, cloud computing, and software engineering.

ML 130

ML ML AWS AI 130

Pickl AI

NOVEMBER 12, 2024

Introduction Embedded AI is transforming the landscape of technology by enabling devices to process data and make intelligent decisions locally, without relying on cloud computing. This involves: Data Preparation : Collect and preprocess data to ensure it is suitable for training your model.

AI 52

AI AI Deep Learning Deep Learning 52

Becoming Human

MAY 15, 2023

It includes a range of tools and features for data preparation, model training, and deployment, making it an ideal platform for large-scale ML projects. Three of the most popular cloud platforms are Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

Pickl AI

OCTOBER 3, 2024

Data Management Tools These platforms often provide robust data management features that assist in data preparation, cleaning, and augmentation, which are crucial for training effective AI models. These providers are leveraging their expertise in cloud computing and Machine Learning to deliver powerful AIMaaS offerings.

Machine Learning 52

Machine Learning Machine Learning AI AI 52

Pickl AI

NOVEMBER 4, 2024

By implementing efficient data pipelines , organisations can enhance their data processing capabilities, reduce time spent on data preparation, and improve overall data accessibility. Data Storage Solutions Data storage solutions are critical in determining how data is organised, accessed, and managed.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Pickl AI

SEPTEMBER 5, 2024

By leveraging Azure’s capabilities, you can gain the skills and experience needed to excel in this dynamic field and contribute to cutting-edge data solutions. Microsoft Azure, often referred to as Azure, is a robust cloud computing platform developed by Microsoft. What is Azure?

Azure 52

Azure Data Scientist Data Science Machine Learning 52

The MLOps Blog

JUNE 27, 2023

See also Thoughtworks’s guide to Evaluating MLOps Platforms End-to-end MLOps platforms End-to-end MLOps platforms provide a unified ecosystem that streamlines the entire ML workflow, from data preparation and model development to deployment and monitoring. Severless GPUs are machines that scale-to-zero in the absence of traffic.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

AWS Machine Learning Blog

JANUARY 26, 2024

This is backed by our deep set of over 300 cloud security tools and the trust of our millions of customers, including the most security-sensitive organizations like government, healthcare, and financial services.

AWS 140

AWS ML ML AI 140

AWS Machine Learning Blog

NOVEMBER 27, 2024

This approach to data preparation creates the foundation for fine-tuning a model that can play chess at a high level. Fine-tune a model With our refined dataset prepared from successful games and legal moves, we now proceed to fine-tune a model using Amazon SageMaker JumpStart.

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AWS AI AI Python 129