Azure, Clustering and Demo - Data Science Current

6 AI tools revolutionizing data analysis: Unleashing the best in business

Data Science Dojo

JULY 17, 2023

Scikit-learn can be used for a variety of data analysis tasks, including: Classification Regression Clustering Dimensionality reduction Feature selection Leveraging Scikit-learn in data analysis projects Scikit-learn can be used in a variety of data analysis projects. It is open-source, so it is free to use and modify.

Data Analysis

Data Analysis Data Analysis Tableau Machine Learning

Use GitHub Actions with Azure ML Studio: train, deploy/publish, monitor

Mlearning.ai

AUGUST 28, 2023

I recently took the Azure Data Scientist Associate certification exam DP-100, thankfully I passed after about 3–4 months for studying the Microsoft Data Science Learning Path and the Coursera Microsoft Azure Data Scientist Associate Specialization. Resources include the: Resource group, Azure ML studio, Azure Compute Cluster.

Azure

Azure ML ML Data Science

Get Creative with AI Forecasting in Changing Economic Conditions

DataRobot Blog

OCTOBER 4, 2022

In this blog, we’ll review the DataRobot new Time Series clustering feature, which gives you a creative edge to build time series forecasting models by automatically grouping series that are identical to each other and then building models tailored to these groups. You can also connect to Snowflake, Azure, Redshift and many other databases.

Clustering

Clustering AI AI Azure

Webinars

What’s New in Apache Airflow® 3.0—And How Will It Reshape Your Data Workflows?

MORE WEBINARS

Citus 12: Schema-based sharding for PostgreSQL

Hacker News

JULY 18, 2023

And if you want to see demos of some of this functionality, be sure to join us for the livestream of the Citus 12.0 Moreover, the cluster can be rebalanced based on disk usage, such that large schemas automatically get more resources dedicated to them, while small schemas are efficiently packed together. Updates page. metric = alerts.

Database

Database SQL Data Modeling Data Models

Introducing the MLOps Management Agent

DataRobot

JUNE 16, 2021

The MLOps Management Agent provides a framework to automate the entire model deployment lifecycle in any environment or infrastructure such as Azure, GCP, AWS, or your own on-premise Kubernetes cluster. See It Live: Kubernetes Deployment on Azure. What’s the new page , you can find a demo video to see how it works.

Azure

Azure Data Science Clustering AWS

Snorkel Flow Spring 2023: warm starts and foundation models

Snorkel AI

MARCH 30, 2023

If you want to see Snorkel Flow in action, sign up for a demo. Native integrations with Tesseract and Azure Form Recognizer for OCR processing unlock non-native PDF use cases without the need to pre-process data through an external OCR service. Schedule a demo with one of our Snorkel Flow experts. Advanced SDK tools.

ML

ML ML Supervised Learning Azure

Building A Spotify Recommendation App

Mlearning.ai

JULY 9, 2023

I realized that the algorithm assumes that we like a particular genre and artist and groups us into these clusters, not letting us discover and experience new music. I then posted it on github built the app on Azure web pages. While scrolling through my recommended playlist.

Algorithm

Algorithm Azure Clustering ML

Pictures and Highlights from ODSC Europe 2023

ODSC - Open Data Science

JULY 22, 2023

On Wednesday, Henk Boelman, Senior Cloud Advocate at Microsoft, spoke about the current landscape of Microsoft Azure, as well as some interesting use cases and recent developments. You can read the recap here and watch the full keynote here. Expo Hall ODSC events are more than just data science training and networking events.

Apache Kafka

Apache Kafka Machine Learning Machine Learning Data Science

4 Ways to Get Hands-On With Generative AI at ODSC East

ODSC - Open Data Science

APRIL 21, 2023

Keynotes Infuse Generative AI in your apps using Azure OpenAI Service As you know, businesses are always looking for ways to improve efficiency and reduce risk, and one way they’re achieving this is through the integration of large language models. Present your innovative solution to both a live audience and a panel of judges.

AI

AI AI Azure Algorithm

Generative AI in the Enterprise

O'Reilly Media

NOVEMBER 28, 2023

Second, while OpenAI’s GPT-4 announcement last March demoed generating website code from a hand-drawn sketch, that capability wasn’t available until after the survey closed. Third, while roughing out the HTML and JavaScript for a simple website makes a great demo, that isn’t really the problem web designers need to solve.

AI

AI AI Data Analysis Data Analysis

MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

JUNE 27, 2023

Microsoft Azure ML Platform The Azure Machine Learning platform provides a collaborative workspace that supports various programming languages and frameworks. Kubeflow integrates with popular ML frameworks, supports versioning and collaboration, and simplifies the deployment and management of ML pipelines on Kubernetes clusters.

Machine Learning

Machine Learning Machine Learning ML ML

Top 50+ Data Analyst Interview Questions & Answers

Pickl AI

APRIL 26, 2024

Then, I would use clustering techniques such as k-means or hierarchical clustering to group customers based on similarities in their purchasing behaviour. Have you worked with cloud-based data platforms like AWS, Google Cloud, or Azure? Additional Benefits Free demo sessions. What approach would you take?

Data Analyst

Data Analyst Data Analysis Data Analysis Machine Learning

Deploying ML Models on GPU With Kyle Morris

The MLOps Blog

DECEMBER 29, 2022

How do you look at an On-Premises GPU cluster, managed by NVIDIA AI enterprise software suite in combination with Red Hat OpenShift or VMware Tanzu, over something like AWS stack or Azure stack for the same GPU cluster managed by EKS, for example? Kyle: I want to make sure I get this. You can get the best of both worlds.

ML

ML ML Machine Learning Machine Learning

Definite Guide to Building a Machine Learning Platform

The MLOps Blog

MARCH 21, 2023

We ask this during product demos, user and support calls, and on our MLOps LIVE podcast. Orchestrators are concerned with lower-level abstractions like machines, instances, clusters, service-level grouping, replication, and so on. Why are you building an ML platform?

Machine Learning

Machine Learning Machine Learning Data Scientist ML

Learnings From Building the ML Platform at Mailchimp

The MLOps Blog

OCTOBER 3, 2023

For example, you can use BigQuery , AWS , or Azure. It can be a cluster run by Kubernetes or maybe something else. In terms of the interaction, ideally, the data scientists shouldn’t have to be setting up infrastructure like a Spark cluster. It’s almost like a specialized data processing and storage solution.

ML

ML ML Data Scientist Machine Learning

Data Science Current

6 AI tools revolutionizing data analysis: Unleashing the best in business

Use GitHub Actions with Azure ML Studio: train, deploy/publish, monitor

Webinars

Trending Sources

Get Creative with AI Forecasting in Changing Economic Conditions

Webinars

Citus 12: Schema-based sharding for PostgreSQL

Introducing the MLOps Management Agent

Snorkel Flow Spring 2023: warm starts and foundation models

Building A Spotify Recommendation App

Pictures and Highlights from ODSC Europe 2023

4 Ways to Get Hands-On With Generative AI at ODSC East

Generative AI in the Enterprise

MLOps Landscape in 2023: Top Tools and Platforms

Top 50+ Data Analyst Interview Questions & Answers

Deploying ML Models on GPU With Kyle Morris

Definite Guide to Building a Machine Learning Platform

Learnings From Building the ML Platform at Mailchimp

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