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. When uploading your data, you specify the Machine Learning type, test, and training data before training. Let us get started!

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Pickl AI

SEPTEMBER 5, 2024

Summary: This blog provides a comprehensive roadmap for aspiring Azure Data Scientists, outlining the essential skills, certifications, and steps to build a successful career in Data Science using Microsoft Azure. What is Azure?

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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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Data Science Dojo

SEPTEMBER 10, 2024

Open AI In the rapidly evolving field of artificial intelligence, OpenAI stands out as a leading force in the LLM world. Additionally, Azure Machine Learning enables the operationalization and management of large language models, providing a robust platform for developing and deploying AI solutions.

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Towards AI

MARCH 28, 2024

Building an Enterprise Data Lake with Snowflake Data Cloud & Azure using the SDLS Framework. By Richie Bachala This blog delves into the intricacies of building these critical data ingestion designs into Snowflake Data Cloud for enterprises. Think a friend would enjoy this too?

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IBM Journey to AI blog

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Data fabric: A mostly new architecture.

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ODSC - Open Data Science

APRIL 27, 2023

Building a Capability Roadmap: The Maturity Stages of Data & AI To manage the gaining value of AI investments, most leaders have created a plan of attack in the form of a capability roadmap that addresses those challenges in order of priority and dependency. What are the benefits of this technology, and how can you apply it?

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ODSC - Open Data Science

AUGUST 24, 2023

ODSC West Call for Volunteers October 30th to November 2nd Our Volunteer program is a great way to get involved in ODSC — one of the world’s largest conferences and communities of artificial intelligence and data science experts.

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ODSC - Open Data Science

FEBRUARY 2, 2023

Big data isn’t an abstract concept anymore, as so much data comes from social media, healthcare data, and customer records, so knowing how to parse all of that is needed. This pushes into big data as well, as many companies now have significant amounts of data and large data lakes that need analyzing.

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Pickl AI

DECEMBER 2, 2024

As organisations grapple with this vast amount of information, understanding the main components of Big Data becomes essential for leveraging its potential effectively. Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets.

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ODSC - Open Data Science

OCTOBER 25, 2024

Building an Open, Governed Lakehouse with Apache Iceberg and Apache Polaris (Incubating) Yufei Gu | Senior Software Engineer | Snowflake In this session, you’ll explore how open-source table formats are revolutionizing data architectures by enabling the power and efficiency of data warehouses within data lakes.

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Alation

JULY 18, 2022

And the highlight, for us data intelligence folks, was the Databricks’ announcement that Unity Catalog , its unified governance solution for all data assets on its Lakehouse platform, will soon be available on AWS and Azure in the upcoming weeks. A simple model to control access to data via a UI or SQL.

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ODSC - Open Data Science

JUNE 12, 2023

Power BI Datamarts provide no-code/low-code datamart capabilities using Azure SQL Database technology in the background. The Power BI Datamarts support sensitivity labels, endorsement, discovery, and Row-Level Security ( RLS ), which help protect and manage the data according to the business requirements and compliance needs.

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Pickl AI

JULY 25, 2024

Data Ingestion Meaning At its core, It refers to the act of absorbing data from multiple sources and transporting it to a destination, such as a database, data warehouse, or data lake. Batch Processing In this method, data is collected over a period and then processed in groups or batches.

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ODSC - Open Data Science

JULY 11, 2023

Conversational artificial intelligence has been around for almost 60 years now. It uses a form of artificial intelligence called Reinforcement Learning from Human Feedback to produce answers based on human-guided computer analytics.2 They are typically used by organizations to store and manage their own data.

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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. Expo Hall ODSC events are more than just data science training and networking events. You can read the recap here and watch the full keynote here.

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Pickl AI

MARCH 10, 2025

Scalability for Large Datasets Power BI can handle massive datasets efficiently using its in-memory analytics engine and Azure integration. Example: A manufacturing company analyses sensor data from production facilities to predict equipment failures and optimise operations. Impact: Scales seamlessly as organisational data grows.

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DagsHub

NOVEMBER 11, 2024

Social media conversations, comments, customer reviews, and image data are unstructured in nature and hold valuable insights, many of which are still being uncovered through advanced techniques like Natural Language Processing (NLP) and machine learning. Many find themselves swamped by the volume and complexity of unstructured data.

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ODSC - Open Data Science

JANUARY 18, 2024

So as you take inventory of your existing skill set, you’ll want to start to identify the areas where you need to focus on to become a data engineer. These areas may include SQL, database design, data warehousing, distributed systems, cloud platforms (AWS, Azure, GCP), and data pipelines. Learn more about the cloud.

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ODSC - Open Data Science

APRIL 3, 2023

Data analysts often must go out and find their data, process it, clean it, and get it ready for analysis. This pushes into Big Data as well, as many companies now have significant amounts of data and large data lakes that need analyzing. Cloud Services: Google Cloud Platform, AWS, Azure.

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ODSC - Open Data Science

OCTOBER 3, 2024

AI and Data: Enhancing Development with GitHub Copilot How can GitHub Copilot be used in environments like Visual Studio Code, JetBrains IDEs, or Azure Data Studio to significantly reduce coding time? Industry, Opinion, Career Advice AI for Robotics and Autonomy with Francis X.

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AWS Machine Learning Blog

DECEMBER 20, 2023

A novel approach to solve this complex security analytics scenario combines the ingestion and storage of security data using Amazon Security Lake and analyzing the security data with machine learning (ML) using Amazon SageMaker.

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ODSC - Open Data Science

OCTOBER 20, 2023

At the AI Expo and Demo Hall as part of ODSC West in a few weeks, you’ll have the opportunity to meet one-on-one with representatives from industry-leading organizations like Microsoft Azure, Hewlett Packard, Iguazio, neo4j, Tangent Works, Qwak, Cloudera, and others.

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The MLOps Blog

MARCH 21, 2023

Solution Data lakes and warehouses are the two key components of any data pipeline. The data lake is a platform where any kind or amount of data can be stored, processed, and analyzed. Data engineers are mostly in charge of it. Data Lake Vs. Feature Store.

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Flipboard

JUNE 16, 2025

Microsoft Azure Cosmos DB is a globally distributed, multi-model database with enough intelligence to be able to manage structured, semi-structured and unstructured data. The natural evolution for a data market like this is the arrival of industry-specific services aligned to industry verticals.

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