Flipboard

JUNE 20, 2023

Machine learning (ML) engineers have traditionally focused on striking a balance between model training and deployment cost vs. performance. This is important because training ML models and then using the trained models to make predictions (inference) can be highly energy-intensive tasks.

Machine Learning 94

Machine Learning BERT Deep Learning ML Engineer 94

AWS Machine Learning Blog

DECEMBER 1, 2023

Launched in 2019, Amazon SageMaker Studio provides one place for all end-to-end machine learning (ML) workflows, from data preparation, building and experimentation, training, hosting, and monitoring. About the Authors Mair Hasco is an AI/ML Specialist for Amazon SageMaker Studio. She is also the author of a book on computer vision.

ML 96

ML Machine Learning DevOps Computer Vision 96

TheSequence

MAY 21, 2023

🔎 ML Research RL for Open Ended LLM Conversations Google Research published a paper detailing dynamic planning, a reinforcement learning(RL) based technique to guide open ended conversations. Visual Layer announced a $7 million round to help enterprises manage datasets for computer vision models. Union AI raised $19.1

Generative AI 64

Generative AI ML Engineer ETL LLM 64

Viso.ai

JANUARY 30, 2024

” We will cover the most important model training errors, such as: Overfitting and Underfitting Data Imbalance Data Leakage Outliers and Minima Data and Labeling Problems Data Drift Lack of Model Experimentation About us: At viso.ai, we offer the Viso Suite, the first end-to-end computer vision platform. Model Error No.

Data Drift 52

Data Drift Machine Learning Computer Vision Algorithm 52

Towards AI

APRIL 27, 2023

Because selecting it judicially reduces the data movement, data processing computation, and data labeling costs downstream Then once the data is collected, synchronized, and selected, it needs to be labeled, which, again, no one from the AI team wants to do. SAM from Meta AI — the chatGPT moment for computer vision AI It’s a disruption.

Automation 87

Automation Auto-complete Computer Vision ML Engineer 87

AWS Machine Learning Blog

NOVEMBER 16, 2023

Amazon SageMaker provides purpose-built tools for machine learning operations (MLOps) to help automate and standardize processes across the ML lifecycle. In this post, we describe how Philips partnered with AWS to develop AI ToolSuite—a scalable, secure, and compliant ML platform on SageMaker.

Data Scientist 89

Data Scientist ML Data Science Automation 89

Snorkel AI

MAY 4, 2023

Reinforcement learning has shown great promise in mastering complex games and decision-making tasks, while computer vision has progressed rapidly, allowing for more accurate image recognition, object detection, and scene understanding. Enterprise use cases: predictive AI, generative AI, NLP, computer vision, conversational AI.

Computer Vision 52

Computer Vision Large Language Models AI AI 52

Snorkel AI

MAY 4, 2023

Reinforcement learning has shown great promise in mastering complex games and decision-making tasks, while computer vision has progressed rapidly, allowing for more accurate image recognition, object detection, and scene understanding. Enterprise use cases: predictive AI, generative AI, NLP, computer vision, conversational AI.

Computer Vision 52

Computer Vision Large Language Models AI AI 52

ODSC - Open Data Science

JANUARY 10, 2024

Takeaways include: The dangers of using post-hoc explainability methods as tools for decision-making, and where traditional ML falls short. Participants will walk away with a solid grasp of feature stores, equipped with the knowledge to drive meaningful insights and enhancements in their real-world ML platforms and projects.

Large Language Models 52

Large Language Models LLM Deep Learning ML 52

Chatbots Life

MAY 16, 2023

10Clouds is a software consultancy, development, ML, and design house based in Warsaw, Poland. Services : AI Solution Development, ML Engineering, Data Science Consulting, NLP, AI Model Development, AI Strategic Consulting, Computer Vision. Elite Service Delivery partner of NVIDIA.

Generative AI 98

Generative AI Chatbots Conversational AI Software Development 98

Heartbeat

OCTOBER 23, 2023

The Role of Data Scientists and ML Engineers in Health Informatics At the heart of the Age of Health Informatics are data scientists and ML engineers who play a critical role in harnessing the power of data and developing intelligent algorithms. We pay our contributors, and we don't sell ads.

Data Scientist 52

Data Scientist Machine Learning Big Data Algorithm 52

AWS Machine Learning Blog

MARCH 22, 2023

Generating this data can take months to gather and require large teams of labelers to prepare it for use in machine learning (ML). Behind the scenes, Rekognition Custom Labels automatically loads and inspects the training data, selects the right ML algorithms, trains a model, and provides model performance metrics.

Automation 80

Automation Machine Learning ML Computer Vision 80

Flipboard

MARCH 13, 2023

With terabytes of data generated by the product, the security analytics team focuses on building machine learning (ML) solutions to surface critical attacks and spotlight emerging threats from noise. Solution overview The following diagram illustrates the ML platform architecture.

Data Scientist 102

Data Scientist Auto-complete ML Machine Learning 102

Snorkel AI

JUNE 9, 2023

Accelerate ML Adoption by Addressing Hidden Needs Max Williams, AI platform product manager at Wells Fargo , discussed the challenges of achieving a return on investment in machine learning as well as the hidden needs an organization must address for ML to gain widespread adoption and deliver attractive returns.

Large Language Models 52

Large Language Models Data Scientist Machine Learning Computer Vision 52

Snorkel AI

JUNE 9, 2023

Accelerate ML Adoption by Addressing Hidden Needs Max Williams, AI platform product manager at Wells Fargo , discussed the challenges of achieving a return on investment in machine learning as well as the hidden needs an organization must address for ML to gain widespread adoption and deliver attractive returns.

Large Language Models 52

Large Language Models Data Scientist Machine Learning Computer Vision 52

Heartbeat

OCTOBER 5, 2023

Unsurprisingly, Machine Learning (ML) has seen remarkable progress, revolutionizing industries and how we interact with technology. Where is LLMOps in DevOps and MLOps In MLOps, engineers are dedicated to enhancing the efficiency and impact of ML model deployment. The focus shifts towards prompt engineering and fine-tuning.

Large Language Models 52

Large Language Models DevOps Prompt Engineer Prompt Engineering 52

The MLOps Blog

OCTOBER 3, 2023

This article was originally an episode of the ML Platform Podcast , a show where Piotr Niedźwiedź and Aurimas Griciūnas, together with ML platform professionals, discuss design choices, best practices, example tool stacks, and real-world learnings from some of the best ML platform professionals. How do I develop my body of work?

ML 52

ML Data Scientist Machine Learning Data Science 52

AWS Machine Learning Blog

MAY 5, 2023

Voxel51 is the company behind FiftyOne, the open-source toolkit for building high-quality datasets and computer vision models. Solution overview Ground Truth is a fully self-served and managed data labeling service that empowers data scientists, machine learning (ML) engineers, and researchers to build high-quality datasets.

Metadata 75

Metadata Computer Vision Machine Learning Data Scientist 75

The MLOps Blog

MARCH 28, 2023

And because it takes more than technologies and processes to succeed with MLOps, he will also share details on: 1 Brainly’s ML use cases, 2 MLOps culture, 3 Team structure, 4 And technologies Brainly uses to deliver AI services to its clients, Enjoy the article! Multiple AI teams also contribute to ML infrastructure initiatives.

Machine Learning 59

Machine Learning Automation Data Scientist ML 59

AWS Machine Learning Blog

FEBRUARY 9, 2023

SageMaker now supports geospatial machine learning (ML), making it easier for data scientists and ML engineers to build, train, and deploy models using geospatial data. In this post, we showed how to acquire data, perform analysis, and visualize the changes with SageMaker geospatial AI/ML services.

Machine Learning 55

Machine Learning ML Deep Learning Robotics 55

Flipboard

SEPTEMBER 4, 2023

Envision yourself as an ML Engineer at one of the world’s largest companies. You make a Machine Learning (ML) pipeline that does everything, from gathering and preparing data to making predictions. Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated?

Machine Learning 109

Machine Learning Computer Vision Deep Learning Python 109

Allen AI

NOVEMBER 8, 2023

Patrick Beukema is the Lead ML Engineer for Skylight Patrick Beukema is the Lead ML Engineer for Skylight. I joined Skylight as head of ML, and it has proven to be a dream role. We are looking forward to traveling to New Orleans this year for NeurIPS and the inaugural Computational Sustainability workshop.

Computer Vision 52

Computer Vision ML Engineer ML Neural Network 52

The MLOps Blog

NOVEMBER 14, 2023

This is where visualizations in ML come in. Visualizing deep learning models can help us with several different objectives: Interpretability and explainability: The performance of deep learning models is, at times, staggering, even for seasoned data scientists and ML engineers. Which one is right for you depends on your goal.

Deep Learning 111

Deep Learning Neural Network Convolutional Neural Networks Data Scientist 111

BAIR

MARCH 11, 2024

Their work at BAIR, ranging from deep learning, robotics, and natural language processing to computer vision, security, and much more, has contributed significantly to their fields and has had transformative impacts on society. Specifically, I work on methods that algorithmically generates diverse training environments (i.e.,

Robotics 344

Robotics Natural Language Processing Machine Learning Computer Vision 344

Pickl AI

JANUARY 23, 2023

Most of the organizations make use of Caffe in order to deal with computer vision and classification related problems. Theano Theano is one of the fastest and simplest ML libraries, and it was built on top of NumPy. Pros It has various algorithms and even ensemble features that help in prediction of several ML models.

Machine Learning 52

Machine Learning ML Neural Network Auto-classification 52

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.

DevOps 94

DevOps ML Machine Learning Automation 94

AWS Machine Learning Blog

MARCH 13, 2024

The audio moderation workflow uses Amazon Transcribe Toxicity Detection, which is a machine learning (ML)-powered capability that uses audio and text-based cues to identify and classify voice-based toxic content across seven categories, including sexual harassment, hate speech, threats, abuse, profanity, insults, and graphic language.

LLM 107

LLM Natural Language Processing Prompt Engineer Prompt Engineering 107

AWS Machine Learning Blog

NOVEMBER 30, 2023

Code Editor is based on Code-OSS , Visual Studio Code Open Source, and provides access to the familiar environment and tools of the popular IDE that machine learning (ML) developers know and love, fully integrated with the broader SageMaker Studio feature set. Choose Open CodeEditor to launch the IDE.

Machine Learning 102

Machine Learning ML LLM Software Engineer 102

AWS Machine Learning Blog

OCTOBER 2, 2023

A successful deployment of a machine learning (ML) model in a production environment heavily relies on an end-to-end ML pipeline. Although developing such a pipeline can be challenging, it becomes even more complex when dealing with an edge ML use case. This helps avoid costly defects at later stages of the production process.

DevOps 91

DevOps Automation ML Computer Vision 91

Viso.ai

FEBRUARY 27, 2024

Since its inception in 2015, the YOLO (You Only Look Once) object-detection algorithm has been closely followed by tech enthusiasts, data scientists, ML engineers, and more, gaining a massive following due to its open-source nature and community contributions. Viso Suite is the end-to-end platform for no code computer vision.

Neural Network 52

Neural Network Computer Vision Convolutional Neural Networks Python 52

Snorkel AI

OCTOBER 12, 2023

Discover the strategies used to drive data-driven decisions within the complex governmental landscape and gain valuable perspectives on the future of AI/ML, the ethical considerations in data science, and the transformative potential of leveraging data to better society. Current specialized ML libraries (e.g.,

Data Scientist 64

Data Scientist AI AI ML 64

Flipboard

OCTOBER 9, 2023

Getting Used to Docker for Machine Learning Introduction Docker is a powerful addition to any development environment, and this especially rings true for ML Engineers or enthusiasts who want to get started with experimentation without having to go through the hassle of setting up several drivers, packages, and more.

Machine Learning 116

Machine Learning Computer Vision Deep Learning Python 116

AWS Machine Learning Blog

APRIL 19, 2023

Businesses are increasingly using machine learning (ML) to make near-real-time decisions, such as placing an ad, assigning a driver, recommending a product, or even dynamically pricing products and services. As a result, some enterprises have spent millions of dollars inventing their own proprietary infrastructure for feature management.

ML 77

ML Data Scientist Big Data Machine Learning 77

Snorkel AI

OCTOBER 12, 2023

Discover the strategies used to drive data-driven decisions within the complex governmental landscape and gain valuable perspectives on the future of AI/ML, the ethical considerations in data science, and the transformative potential of leveraging data to better society. Current specialized ML libraries (e.g.,

Data Scientist 59

Data Scientist AI AI ML 59

ODSC - Open Data Science

JULY 19, 2023

Machine Learning Operations (MLOps) can significantly accelerate how data scientists and ML engineers meet organizational needs. A well-implemented MLOps process not only expedites the transition from testing to production but also offers ownership, lineage, and historical data about ML artifacts used within the team.

Machine Learning 52

Machine Learning Data Drift Data Science ML Engineer 52

AWS Machine Learning Blog

SEPTEMBER 29, 2023

In this post, we illustrate how to use a segmentation machine learning (ML) model to identify crop and non-crop regions in an image. Identifying crop regions is a core step towards gaining agricultural insights, and the combination of rich geospatial data and ML can lead to insights that drive decisions and actions.

Machine Learning 112

Machine Learning ML Data Scientist Python 112

The MLOps Blog

AUGUST 11, 2023

There comes a time when every ML practitioner realizes that training a model in Jupyter Notebook is just one small part of the entire project. At that point, the Data Scientists or ML Engineers become curious and start looking for such implementations. What are ML pipeline architecture design patterns?

ML 52

ML Machine Learning Data Ingestion Deep Learning 52