Data Science Dojo

JANUARY 22, 2025

To get you started, Data Science Dojo and Weaviate have teamed up to bring you an exciting webinar series: Master Vector Embeddings with Weaviate. Whether you’re just starting or looking to refine your expertise, this webinar series is your gateway to the true potential of vector embeddings.

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KDnuggets

NOVEMBER 18, 2019

Join this live webinar from cnvrg, Continual Learning with Human-in-the-loop, Nov 26 @ 12 PM EST, and learn the role of human-in-the-loop in your ML pipeline, how to close the loop in your pipeline, and much more.

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DataRobot

MARCH 4, 2020

In a recent webinar, Paxata's Senior Product Marketing Manager Mike White and I demonstrated Paxata's unique ability to eliminate the most common bottleneck in AI and machine learning.

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Flipboard

JUNE 23, 2023

Learn how to use large language models to extract insights from documents for analytics and ML at scale. Join this webinar and live tutorial to learn how to get started.

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Data Science Dojo

APRIL 23, 2025

The answer to this dilemma is Arize AI, the team leading the charge on ML observability and evaluation in production. Part 1 of the webinar series, in partnership with Arize AI, walks you through real-world examples, design patterns, and live demos that bring these concepts to life. Part 3: Can Agents Evaluate Themselves?

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DagsHub

MARCH 3, 2024

In this DagsHub community webinar, Pavlo Fesenko explores the world of video classification and model deployment. This is a practical session for enthusiasts and ML professionals alike! Learn to deploy machine learning models using AWS's free tools, create automated CI/CD pipelines, and master MLflow's model registry.

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Iguazio

APRIL 28, 2025

You can hear more details in the webinar this article is based on, straight from Kaegan Casey, AI/ML Solutions Architect at Seagate. Iguazio allows sharing projects between diverse teams, provides detailed logging of parameters, metrics, and ML artifacts and allows for artifact versioning including labels, tags, associated data etc.

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Hacker News

AUGUST 4, 2023

We are looking for someone who enjoys performing live on stage via webinars and recorded content. Our ideal candidate for this role should have a background in engineering and software development, proficiency in Python and knowledge of the ML community -- either through attending events, collaborating on open source software

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Flipboard

DECEMBER 18, 2023

Over the last few months, EdSurge webinar host Carl Hooker moderated three webinars featuring field-expert panelists discussing the transformative impact of artificial intelligence in the education field. He also introduces the concept of generative AI (gen AI), which signifies the next step in the evolution of AI and ML.

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phData

DECEMBER 12, 2024

The Snowflake AI Data Cloud has been on a roll, building predictive ML capabilities into their platform. Predictive ML in Snowflake Snowflakes predictive ML platform covers the lifecycle of a typical machine learning project. Watch Webinar The post Snowflake ML Objects Cheatsheet appeared first on phData.

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ODSC - Open Data Science

MARCH 23, 2023

Each month, ODSC has a few insightful webinars that touch on a range of issues that are important in the data science world, from use cases of machine learning models, to new techniques/frameworks, and more. So here’s a summary of a few recent webinars that you’ll want to watch. This is why we want to begin highlighting them for you.

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Flipboard

JUNE 12, 2025

Impact: Companies implementing ML-based lead scoring report up to 20% lift in B2B SaaS conversions by focusing sales efforts on prospects most likely to convert. Impact: Organizations using ML-optimized send timing report 20-25% higher engagement rates compared to traditional scheduling approaches.

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ODSC - Open Data Science

JUNE 12, 2025

10 Media Datasets to Use AI for Film, TV, and More This blog explores a curated list of publicly available film and visual media datasets that data scientists, ML engineers, and researchers can leverage for innovative projects.

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ODSC - Open Data Science

SEPTEMBER 13, 2024

Virtual Webinar: Building Multimodal Question-Answering (RAG) system with Gemini with Lavi Nigam September 26, 2024, 12:00 PM ET In this virtual webinar, you’ll learn how to leverage Gemini’s 2M context window and multimodal (text, image, audio & video) input to build a question-answering system for financial analysis.

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Iguazio

JUNE 9, 2025

The blog is based on the webinar Deploying Gen AI in Production with NVIDIA NIM & MLRun with Amit Bleiweiss, Senior Data Scientist at NVIDIA, and Yaron Haviv, co-founder and CTO and Guy Lecker, ML Engineering Team Lead at Iguazio (acquired by McKinsey). You can watch the entire webinar here.

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ODSC - Open Data Science

MARCH 20, 2025

Webinar: Beyond Basic PromptingUnlocking Prompt Engineering Wednesday, March 26th, 12:00 PMET This free lesson will explore the limitations of basic prompting, use key prompting techniques for better control and accuracy, help you understand the shift from manual prompting to programmatic PE, and more to improve your prompt engineering skills.

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How to Learn Machine Learning

DECEMBER 24, 2024

AWS ML removes traditional barriers to entry while providing professional-grade capabilities. Whether you’re analyzing customer behavior or building complex AI models, AWS ML provides all the tools needed to transform your data into valuable insights and intelligent applications.

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ODSC - Open Data Science

MARCH 13, 2025

Just Do Something with AI: Bridging the Business Communication Gap forML This blog explores how ML practitioners can navigate AI business communication, ensuring AI initiatives align with real businessvalue. What Can You Do With a Free ODSC East ExpoPass?

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ODSC - Open Data Science

FEBRUARY 27, 2025

Spotify | Apple | SoundCloud Video of the Week: Just Do Something with AI: Bridging the Business Communication Gap for ML Practitioners Why do so many AI and machine learning initiatives failnot because of bad models, but due to poor communication?

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ODSC - Open Data Science

FEBRUARY 17, 2023

ChatGPT: The Google Killer, Distributed Training with PyTorch and Azure ML, and Many Models Batch Training Distributed Training with PyTorch and Azure ML Continue reading to learn the simplest way to do distributed training with PyTorch and Azure ML.

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ODSC - Open Data Science

FEBRUARY 10, 2023

Faster Training and Inference Using the Azure Container for PyTorch in Azure ML If you’ve ever wished that you could speed up the training of a large PyTorch model, then this post is for you. In this post, we’ll cover the basics of this new environment, and we’ll show you how you can use it within your Azure ML project.

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AWS Machine Learning Blog

JUNE 27, 2023

When machine learning (ML) models are deployed into production and employed to drive business decisions, the challenge often lies in the operation and management of multiple models. They swiftly began to work on AI/ML capabilities by building image recognition models using Amazon SageMaker.

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AWS Machine Learning Blog

OCTOBER 29, 2024

With a strong background in AI/ML, Ishan specializes in building Generative AI solutions that drive business value. She speaks at internal and external conferences such AWS re:Invent, Women in Manufacturing West, YouTube webinars, and GHC 23. Yanyan graduated from Texas A&M University with a PhD in Electrical Engineering.

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ODSC - Open Data Science

FEBRUARY 23, 2023

Upcoming Webinars: How to build stunning Data Science Web applications in Python Thu, Feb 23, 2023, 12:00 PM — 1:00 PM EST This webinar presents Taipy, a new low-code Python package that allows you to create complete Data Science applications, including graphical visualization and the management of algorithms, models, and pipelines.

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Smart Data Collective

OCTOBER 14, 2021

Some programs are suitable for one-on-one conversations; some are perfect for chats in small groups; while others are capable of handling large webinars and masterclasses involving hundreds of people. . Unique AI and ML-based software. Save missed business meetings, conferences, and webinars to the cloud storage for future playback.

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AWS Machine Learning Blog

MARCH 20, 2025

It often requires managing multiple machine learning (ML) models, designing complex workflows, and integrating diverse data sources into production-ready formats. He speaks at conferences such as AWS re:Invent, IEEE, Consumer Technology Society(CTSoc), YouTube webinars, and other industry conferences like CERAWEEK and ADIPEC.

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ODSC - Open Data Science

APRIL 10, 2023

There are countless blockers that may keep you from getting your ML projects off the ground, including: The time required to understand and stitch together a fragmented ecosystem of low-level, ML-specific packages. The engineering effort involved with building and maintaining infrastructure that can execute large-scale ML workloads.

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AWS Machine Learning Blog

JANUARY 13, 2023

In this post, we show you how Parsons is building its next generation workforce by using machine learning (ML) and artificial intelligence (AI) with AWS DeepRacer in a fun and collaborative way. Parsons is on a mission to make AI/ML a foundation of business across the company. Director Jennifer Bergstrom.

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ODSC - Open Data Science

FEBRUARY 9, 2023

That responsibility usually falls in the hands of a role called Machine Learning (ML) Engineer. Having empathy for your ML Engineering colleagues means helping them meet operational constraints. To continue with this analogy, you might think of the ML Engineer as the data scientist’s “editor.”

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ODSC - Open Data Science

OCTOBER 24, 2024

The Essential Tools for ML Evaluation and Responsible AI There are lots of checkmarks to hit when developing responsible AI, but thankfully, there are many tools for ML evaluation and frameworks designed to support responsible AI development and evaluation. Learn how Informa’s IIRIS team manages data from over 2.5 global trade shows.

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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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AWS Machine Learning Blog

SEPTEMBER 24, 2024

AWS AI and machine learning (ML) services help address these concerns within the industry. AI/ML on AWS AI and ML have been a focus for Amazon for over 25 years, and many of the capabilities customers use with Amazon are driven by ML. Solutions Architect at AWS focusing on AI/ML and generative AI.

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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. Here are a few things to keep an eye out for. 5 Data Engineering and Data Science Cloud Options for 2023 AI development is incredibly resource intensive.

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Flipboard

NOVEMBER 17, 2024

Don’t Forget to join our 55k+ ML SubReddit. FREE AI WEBINAR ] Implementing Intelligent Document Processing with GenAI in Financial Services and Real Estate Transactions – From Framework to Production The post GraphAide: Building and Utilizing Knowledge Graphs for Domain-Specific Digital Assistants appeared first on MarkTechPost.

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ODSC - Open Data Science

APRIL 3, 2025

Democratizing AI: Why Its Not Just a Developers GameAnymore Generative AI is no longer just for ML experts. Tune into one of our webinars to learn about tools, languages, packages, and moreall from leading data scientists. As we hit scaling limits, reasoning marks the next evolution in large languagemodels.

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ODSC - Open Data Science

DECEMBER 7, 2023

Video of the Week: Notion’s ML Engineering: Search & Ranking Models using Snowflake & Qwak Check out this on-demand webinar where Snowflake and Qwak delve deep into the mechanics of Notion’s Search & Ranking Machine Learning Model using Snowflake and Qwak.

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ODSC - Open Data Science

APRIL 13, 2023

4 Reasons Why Declarative ML Makes Sense for Engineers In this blog post, we’re going to cover Ludwig, an open-source declarative ML framework, and four reasons why this approach makes sense for every engineer interested in ML.

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