Marktechpost

JUNE 19, 2024

Generative AI for Data Scientists Specialization This specialization by IBM is designed for data professionals to learn generative AI, including prompt engineering and applying AI tools in data science.

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Artificial Intelligence Artificial Intelligence Prompt Engineer Prompt Engineering 122

Towards AI

FEBRUARY 15, 2024

Author(s): Jennifer Wales Originally published on Towards AI. AI Engineers: Your Definitive Career Roadmap Become a professional certified AI engineer by enrolling in the best AI ML Engineer certifications that help you earn skills to get the highest-paying job.

AI Engineer 111

AI Engineer Software Engineer Artificial Intelligence Artificial Intelligence 111

ODSC - Open Data Science

MARCH 27, 2023

ML Governance: A Lean Approach Ryan Dawson | Principal Data Engineer | Thoughtworks Meissane Chami | Senior ML Engineer | Thoughtworks During this session, you’ll discuss the day-to-day realities of ML Governance. Some of the questions you’ll explore include How much documentation is appropriate?

Machine Learning 98

Machine Learning Data Science Data Ingestion Deep Learning 98

Towards AI

MAY 30, 2024

This book was an incredible guide of how to leverage cutting edge AI models and libraries to build robust tools that minimize the pitfalls of the current technology. This book provides practical insights and real-world applications of, inter alia, RAG systems and prompt engineering. I highly recommend this book.”

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Prompt Engineering Prompt Engineer LLM NLP 108

ODSC - Open Data Science

FEBRUARY 13, 2025

Build a Data Analyst AI Agent fromScratch Daniel Herrera, Principal Developer Advocate atTeradata Daniel Herrera guided attendees through the process of building a data analyst AI agent from the ground up. Cloning NotebookLM with Open WeightsModels Niels Bantilan, Chief ML Engineer atUnion.AI

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Large Language Models AI AI Automation 52

The MLOps Blog

JUNE 27, 2023

Google Cloud Vertex AI Google Cloud Vertex AI provides a unified environment for both automated model development with AutoML and custom model training using popular frameworks. Qwak Qwak is a fully-managed, accessible, and reliable ML platform to develop and deploy models and monitor the entire machine learning pipeline.

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Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

AUGUST 22, 2024

Building a deployment pipeline for generative artificial intelligence (AI) applications at scale is a formidable challenge because of the complexities and unique requirements of these systems. Generative AI models are constantly evolving, with new versions and updates released frequently.

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ODSC - Open Data Science

NOVEMBER 25, 2024

Ali Arsanjani of Google Cloud This year, we had some of the best and brightest in AI deliver keynote talks to a packed room on days 2 and 3 of ODSC West, as well as virtual keynotes for those logging in online.

Data Science 52

Data Science AI Engineer Prompt Engineering Prompt Engineer 52

Pickl AI

AUGUST 28, 2024

Introduction In the rapidly evolving landscape of Machine Learning , Google Cloud’s Vertex AI stands out as a unified platform designed to streamline the entire Machine Learning (ML) workflow. This unified approach enables seamless collaboration among data scientists, data engineers, and ML engineers.

Machine Learning 52

Machine Learning ML Engineer ML Automation 52

ODSC - Open Data Science

FEBRUARY 25, 2025

Generative AI TrackBuild the Future with GenAI Generative AI has captured the worlds attention with tools like ChatGPT, DALL-E, and Stable Diffusion revolutionizing how we create content and automate tasks. Whats Next in AI TrackExplore the Cutting-Edge Stay ahead of the curve with insights into the future of AI.

Data Scientist 52

Data Scientist Machine Learning Large Language Models ML Engineer 52

AWS Machine Learning Blog

OCTOBER 2, 2024

This allows enterprises to track key performance indicators (KPIs) for their generative AI models, such as I/O volumes, latency, and error rates. Opensearch Dashboards provides powerful search and analytical capabilities, allowing teams to dive deeper into generative AI model behavior, user interactions, and system-wide metrics.

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TheSequence

JANUARY 19, 2024

You probably don’t need ML engineers In the last two years, the technical sophistication needed to build with AI has dropped dramatically. At the same time, the capabilities of AI models have grown. ML engineers used to be crucial to AI projects because you needed to train custom models from scratch.

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Prompt Engineer Prompt Engineering Generative AI Large Language Models 59

ODSC - Open Data Science

FEBRUARY 22, 2024

By the end of this session, you’ll have a practical blueprint to efficiently harness feature stores within ML workflows. Using Graphs for Large Feature Engineering Pipelines Wes Madrigal | ML Engineer | Mad Consulting Feature engineering from raw entity-level data is complex, but there are ways to reduce that complexity.

Machine Learning 52

Machine Learning Data Science Python ML 52

ODSC - Open Data Science

JANUARY 10, 2024

Causal AI: from Data to Action Dr. Andre Franca | CTO | connectedFlow Explore the world of Causal AI for data science practitioners, with a focus on understanding cause-and-effect relationships within data to drive optimal decisions. Register for ODSC East today to save 60% on any pass.

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Large Language Models Deep Learning LLM Data Science 52

Chatbots Life

MAY 16, 2023

Deeper Insights has six years of experience in building AI solutions for large enterprise and scale-up clients, a suite of AI models, and data visualization dashboards that enable them to quickly analyze and share insights.

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Generative AI Chatbots Conversational AI Software Development 92

AWS Machine Learning Blog

MAY 13, 2024

This is known as in-context learning , through which a model learns a task from a few provided examples, specifically during prompting and without tuning the model parameters. In the healthcare domain, this bears great potential to vastly expand the capabilities of existing AI models.

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Generative AI Prompt Engineering Prompt Engineer LLM 135

DataRobot Blog

SEPTEMBER 13, 2022

At this level, the data science team will be small or nonexistent. But potential use cases could increase after AI delivers promising results and organizational confidence grows. Businesses will then require more information-literate staff, but they’ll need to contend with an ongoing shortage of data scientists.

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Data Scientist Automation ML Machine Learning 52

Dlabs.ai

OCTOBER 21, 2024

#InsideAI Frequency: Monthly Best for: Business leaders, AI professionals, entrepreneurs, and those interested in practical AI applications Content: Comprehensive coverage of AI, machine learning, and data science developments This newsletter provided by DLabs.AI delivers the most important news to you every month.

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Deep Learning AI AI Machine Learning 52

Snorkel AI

OCTOBER 12, 2023

Chief Data Scientist In this fireside chat as Snorkel AI CEO and co-founder Alex Ratner and DJ Patil, the Former U.S. Chief Data Scientist dive into data science’s history, impact, and challenges in the United States government.

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Data Scientist ML Computer Vision AI 64

Snorkel AI

OCTOBER 12, 2023

Chief Data Scientist In this fireside chat as Snorkel AI CEO and co-founder Alex Ratner and DJ Patil, the Former U.S. Chief Data Scientist dive into data science’s history, impact, and challenges in the United States government.

Data Scientist 59

Data Scientist ML Computer Vision AI 59

Viso.ai

MARCH 29, 2024

MLflow is an open-source platform designed to manage the entire machine learning lifecycle, making it easier for ML Engineers, Data Scientists, Software Developers, and everyone involved in the process. MLOps aims to automate and operationalize ML models, enabling smoother transitions to production and deployment.

Machine Learning 52

Machine Learning ML Automation Data Scientist 52

ODSC - Open Data Science

JANUARY 3, 2025

Selected Training Sessions for Week 1LLMs (Wed 15 JanThu 16Jan) Cracking the Code: How to Choose the Right LLMs Model for Your Project Ivan Lee, CEO and Founder ofDatasaur Selecting the right AI model is a strategic process that requires careful evaluation and optimization to ensure project success.

LLM 40

LLM AI AI Prompt Engineering 40

Snorkel AI

OCTOBER 12, 2023

Chief Data Scientist In this fireside chat as Snorkel AI CEO and co-founder Alex Ratner and DJ Patil, the Former U.S. Chief Data Scientist dive into data science’s history, impact, and challenges in the United States government.

Data Scientist 52

Data Scientist NLP ML Computer Vision 52

Pickl AI

JUNE 6, 2024

Machine Learning (ML) Machine Learning algorithms are like powerful engines, but they rely on clean fuel – clean data – to function effectively. Inaccurate data can lead to biased and unreliable models. Why is Data Scrubbing Important? Where is Data Scrubbing Used?

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Machine Learning Algorithm Business Intelligence Data Quality 40

AWS Machine Learning Blog

SEPTEMBER 1, 2023

These data owners are focused on providing access to their data to multiple business units or teams. Data science team – Data scientists need to focus on creating the best model based on predefined key performance indicators (KPIs) working in notebooks. One of these new notions is the foundation model (FM).

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Generative AI Prompt Engineering Prompt Engineer ML 126

AWS Machine Learning Blog

APRIL 29, 2024

Metaflow overview Metaflow was originally developed at Netflix to enable data scientists and ML engineers to build ML/AI systems quickly and deploy them on production-grade infrastructure. He is also the author of a book, Effective Data Science Infrastructure, published by Manning.

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ML Python Data Scientist Machine Learning 125

AWS Machine Learning Blog

DECEMBER 2, 2024

Today at AWS re:Invent 2024, we are excited to announce the new Container Caching capability in Amazon SageMaker, which significantly reduces the time required to scale generative AI models for inference. In our tests, we’ve seen substantial improvements in scaling times for generative AI model endpoints across various frameworks.

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The MLOps Blog

MARCH 21, 2023

From gathering and processing data to building models through experiments, deploying the best ones, and managing them at scale for continuous value in production—it’s a lot. As the number of ML-powered apps and services grows, it gets overwhelming for data scientists and ML engineers to build and deploy models at scale.

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69

Viso.ai

DECEMBER 21, 2023

As we go down the list, we discuss the key contributions of every AI influencer. Each of these individuals serves as an inspiration for aspiring AI and ML engineers breaking into the field. Cassie Kozyrkov: A Top Voice in Data Science and Analytics Cassie Kozyrkov makes for one of the AI influencers of this decade.

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Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52

AWS Machine Learning Blog

DECEMBER 4, 2024

Organizations are looking to accelerate the process of building new AI solutions. They use fully managed services such as Amazon SageMaker AI to build, train and deploy generative AI models. Oftentimes, they also want to integrate their choice of purpose-built AI development tools to build their models on SageMaker AI.

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ML Generative AI Data Scientist ML Engineer 135

ODSC - Open Data Science

MARCH 11, 2025

About the Author of Adaptive RAG Systems: David vonThenen David is a Senior AI/ML Engineer at DigitalOcean, where hes dedicated to empowering developers to build, scale, and deploy AI/ML models in production.

LLM 52

LLM Metadata Software Engineer Python 52

AWS Machine Learning Blog

DECEMBER 2, 2024

In Part 2 , we provide a detailed, hands-on guide to implementing Fast Model Loader in your LLM deployments. The rapid evolution of LLMs, with some models now using hundreds of billions of parameters, has led to a significant increase in the computational resources and sophisticated infrastructure required to run them effectively.

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Large Language Models Auto-complete Machine Learning LLM 110

Marktechpost

NOVEMBER 14, 2024

Prior he was an ML product leader at Google working across products like Firebase, Google Research and the Google Assistant as well as Vertex AI. While there, Dev was also the first product lead for Kaggle – a data science and machine learning community with over 8 million users worldwide.

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