ODSC - Open Data Science

MARCH 30, 2023

Using Azure ML to Train a Serengeti Data Model, Fast Option Pricing with DL, and How To Connect a GPU to a Container Using Azure ML to Train a Serengeti Data Model for Animal Identification In this article, we will cover how you can train a model using Notebooks in Azure Machine Learning Studio.

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AWS Machine Learning Blog

MARCH 30, 2023

Therefore, it’s no surprise that determining the proficiency of goalkeepers in preventing the ball from entering the net is considered one of the most difficult tasks in football data analysis. The result is a machine learning (ML)-powered insight that allows fans to easily evaluate and compare the goalkeepers’ proficiencies.

Machine Learning 70

Machine Learning Machine Learning AWS Apache Kafka 70

AWS Machine Learning Blog

FEBRUARY 13, 2024

Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, share, and manage features for machine learning (ML) models. Features are inputs to ML models used during training and inference. This dichotomy can be effectively managed using a cross-account setup for the feature store.

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AWS Machine Learning Blog

JANUARY 26, 2024

Generative artificial intelligence (AI) applications built around large language models (LLMs) have demonstrated the potential to create and accelerate economic value for businesses. These five risks are insecure output handling, supply chain vulnerabilities, sensitive information disclosure, excessive agency, and overreliance.

AWS 122

AWS AI AI ML 122

Flipboard

JUNE 26, 2023

Companies are faced with the daunting task of ingesting all this data, cleansing it, and using it to provide outstanding customer experience. Typically, companies ingest data from multiple sources into their data lake to derive valuable insights from the data. Run the AWS Glue ML transform job.

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Data Science 101

NOVEMBER 11, 2019

It combines data warehousing and data lakes into a simple query interface for a simple and fast analytics service. Data Science Announcements from Microsoft Ignite Many other services were announced such as: Azure Quantum, Project Silica, R support in Azure ML, and Visual Studio Online. Amazon Web Services.

Cloud Data 95

Cloud Data Data Science Azure Clustering 95

Data Science Connect

JULY 28, 2023

Cloud-Based IoT Platforms Cloud-based IoT platforms offer scalable storage and computing resources for handling the massive influx of IoT data. These platforms provide data engineers with the flexibility to develop and deploy IoT applications efficiently.

Internet of Things 130

Internet of Things Data Engineering Data Engineer Data Engineering 130

IBM Journey to AI blog

APRIL 9, 2024

This allows the Masters to scale analytics and AI wherever their data resides, through open formats and integration with existing databases and tools. “Hole distances and pin positions vary from round to round and year to year; these factors are important as we stage the data.”

AI 88

AI AI Machine Learning Machine Learning 88

ODSC - Open Data Science

JUNE 7, 2023

Bilokon | Visiting Lecturer, CEO and Founder | Imperial College London, Thalesians Ltd Apache Kafka for Real-Time Machine Learning Without a Data Lake: Kai Waehner | Global Field CTO, Author, International Speaker Semantic Analysis and Procedural Language Understanding in the Era of Large Language Models: Dr. Gözde Gül Şahin | Assistant Professor, (..)

Apache Kafka 52

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ODSC - Open Data Science

AUGUST 24, 2023

Start Learning AI With the ODSC West Data Primer Series In this six-part series as part of the ODSC West mini-bootcamp, you’ll learn everything you need to know to get started with AI, including SQL, machine learning, and even LLMs. But it doesn’t stop there.

Data Lakes 52

Data Lakes Data Science Machine Learning Machine Learning 52

ODSC - Open Data Science

MAY 31, 2023

Be sure to check out his talk, “ Apache Kafka for Real-Time Machine Learning Without a Data Lake ,” there! The combination of data streaming and machine learning (ML) enables you to build one scalable, reliable, but also simple infrastructure for all machine learning tasks using the Apache Kafka ecosystem.

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Data Lakes Machine Learning Machine Learning Apache Kafka 131

IBM Journey to AI blog

JANUARY 19, 2024

Staying ahead of key technology trends By now, it’s abundantly clear that technologies like artificial intelligence (AI) and machine learning (ML) will revolutionize how customer-centric organizations interact and deliver value to all stakeholders, especially their customers.

Artificial Intelligence 96

Artificial Intelligence Artificial Intelligence ML ML 96

Towards AI

MARCH 28, 2024

Elymsyr wants to develop new projects to improve their ML, RL, computer vision, and co-working skills. Streamline ML Workflow with MLflow — II by ronilpatil This article explains how to leverage MLflow to track machine learning experiments, register a model, and serve the model into production.

AI 75

AI AI Data Lakes Azure 75

ODSC - Open Data Science

JULY 14, 2023

AI and Bias: How to Detect It and How to Prevent It Sandra Wachter, PhD | Professor, Technology and Regulation | Oxford Internet Institute, University of Oxford In recognition of the extensive biases and inequality that are present in training data, there has been much work done to test for bias in machine learning and AI systems.

Machine Learning 52

Machine Learning Machine Learning Apache Kafka Data Science 52

AWS Machine Learning Blog

AUGUST 4, 2023

If you are a returning user to SageMaker Studio, in order to ensure Salesforce Data Cloud is enabled, upgrade to the latest Jupyter and SageMaker Data Wrangler kernels. This completes the setup to enable data access from Salesforce Data Cloud to SageMaker Studio to build AI and machine learning (ML) models.

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ML ML AWS AI 78

AWS Machine Learning Blog

MARCH 1, 2023

Flywheel creates a data lake (in Amazon S3) in your account where all the training and test data for all versions of the model are managed and stored. Periodically, the new labeled data (to retrain the model) can be made available to flywheel by creating datasets. One for the data lake for Comprehend flywheel.

Data Lakes 68

Data Lakes AWS ML ML 68

ODSC - Open Data Science

FEBRUARY 2, 2023

Just as a writer needs to know core skills like sentence structure, grammar, and so on, data scientists at all levels should know core data science skills like programming, computer science, algorithms, and so on. As MLOps become more relevant to ML demand for strong software architecture skills will increase as well.

Data Science 98

Data Science Data Scientist Computer Science Computer Science 98

ODSC - Open Data Science

JULY 22, 2023

We had bigger sessions on getting started with machine learning or SQL, up to advanced topics in NLP, and how to make deepfakes.

Apache Kafka 52

Apache Kafka Machine Learning Machine Learning Data Science 52

AWS Machine Learning Blog

NOVEMBER 22, 2023

Harness a flywheel approach, wherein continuous data feedback is utilized to routinely orchestrate and evaluate enhancements to your models and processes. Enhance IDP with Amazon Comprehend Flywheel and Amazon Textract Custom Queries Leverage the Amazon Comprehend flywheel for a streamlined ML process, from data ingestion to deployment.

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AWS ML ML Machine Learning 83

ODSC - Open Data Science

OCTOBER 20, 2023

You’ll also learn about the latest tools in NLP, machine learning, MLOps, and more during the Solution Talks. You’ll use MLRun, Langchain, and Milvus for this exercise and cover topics like the integration of AI/ML applications, leveraging Python SDKs, as well as building, testing, and tuning your work.

AI 52

AI AI Data Science Machine Learning 52

ODSC - Open Data Science

MARCH 11, 2024

Deploying Trustworthy Generative AI Stable Diffusion: Advancing the Text-to-Image Paradigm Multimodal Retrieval Augmented Generation Machine Learning This track gathers together the creators and top practitioners in the rapidly expanding fields of deep learning and machine learning to discuss the latest advances, trends, and models in these fields.

Deep Learning 52

Deep Learning Deep Learning Data Science AI 52

IBM Journey to AI blog

OCTOBER 16, 2023

Artificial intelligence (AI) adoption is still in its early stages. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. An AI governance framework ensures the ethical, responsible and transparent use of AI and machine learning (ML).

AI 78

AI AI Data Warehouse ML 78

AWS Machine Learning Blog

NOVEMBER 22, 2023

Now all you need is some guidance on generative AI and machine learning (ML) sessions to attend at this twelfth edition of re:Invent. Third, a number of sessions will be of interest to ML practitioners who build, deploy, and operationalize both traditional and generative AI models.

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Smart Data Collective

FEBRUARY 20, 2022

Data storage databases. Your SaaS company can store and protect any amount of data using Amazon Simple Storage Service (S3), which is ideal for data lakes, cloud-native applications, and mobile apps. Artificial intelligence (AI). Well, let’s find out.

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AWS Cloud Computing Data Lakes Database 115

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.

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AWS Machine Learning Blog

AUGUST 2, 2023

Amazon Kendra is an intelligent search service powered by machine learning (ML). Amazon Kendra supports a variety of document formats , such as Microsoft Word, PDF, and text from various data sources. About the Authors Charalampos Grouzakis is a Data Scientist within AWS Professional Services.

AWS 71

AWS AI AI Machine Learning 71

ODSC - Open Data Science

JUNE 7, 2023

To make your data management processes easier, here’s a primer on data lakes, and our picks for a few data lake vendors worth considering. What is a data lake? First, a data lake is a centralized repository that allows users or an organization to store and analyze large volumes of data.

Data Lakes 52

Data Lakes Azure Hadoop Data Warehouse 52

ODSC - Open Data Science

APRIL 3, 2023

This pushes into Big Data as well, as many companies now have significant amounts of data and large data lakes that need analyzing. While there’s a need for analyzing smaller datasets on your laptop, expanding into TB+ datasets requires a whole new set of skills and data analytics frameworks.

Analytics 52

Analytics Analytics Data Analyst SQL 52

IBM Journey to AI blog

APRIL 25, 2023

Relational databases were adapted to accommodate the demands of new workloads, such as the data engineering tasks associated with structured and semi-structured data, and for building machine learning models. To effectively use raw data, it often needs to be curated within a data warehouse.

Data Warehouse 57

Data Warehouse Data Engineering Data Engineer Data Engineering 57

Flipboard

NOVEMBER 24, 2023

With that, the need for data scientists and machine learning (ML) engineers has grown significantly. Data scientists and ML engineers require capable tooling and sufficient compute for their work. Data scientists and ML engineers require capable tooling and sufficient compute for their work.

ML 95

ML ML AWS AI 95

Towards AI

FEBRUARY 13, 2023

According to Yann LeCun, Chief Artificial Intelligence Scientist at Meta, the reason it was boring was that it was made safe. Three months before ChatGPT’s launch in November, Meta, Facebook’s parent company, introduced a similar chatbot, Blenderbot. However, Blenderbot failed to create the same excitement as ChatGPT.

AI 90

AI AI Data Warehouse Data Lakes 90

AWS Machine Learning Blog

JUNE 13, 2023

The combination of large language models (LLMs), including the ease of integration that Amazon Bedrock offers, and a scalable, domain-oriented data infrastructure positions this as an intelligent method of tapping into the abundant information held in various analytics databases and data lakes.

Database 72

Database SQL AWS AI 72

ODSC - Open Data Science

MAY 8, 2023

Article on Azure ML by Bethany Jepchumba and Josh Ndemenge of Microsoft In this article, I will cover how you can train a model using Notebooks in Azure Machine Learning Studio. At the end of this article, you will learn how to use Pytorch pretrained DenseNet 201 model to classify different animals into 48 distinct categories.

Azure 52

Azure ML ML Data Modeling 52

Flipboard

OCTOBER 25, 2023

By some estimates, unstructured data can make up to 80–90% of all new enterprise data and is growing many times faster than structured data. After decades of digitizing everything in your enterprise, you may have an enormous amount of data, but with dormant value. These services write the output to a data lake.

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AWS ML ML Analytics 132

ODSC - Open Data Science

APRIL 27, 2023

5 Concerns for ML Safety in the Era of LLMs and Generative AI The growth of large language models and generative AI has spurred new concerns for ML safety and cybersecurity. 5 Data Engineering and Data Science Cloud Options for 2023 AI development is incredibly resource intensive.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

AWS Machine Learning Blog

MARCH 1, 2023

This combination of great models and continuous adaptation is what will lead to a successful machine learning (ML) strategy. Today, we are excited to announce the launch of Amazon Comprehend flywheel—a one-stop machine learning operations (MLOps) feature for an Amazon Comprehend model.

Data Lakes 84

Data Lakes AWS ML ML 84

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022.

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