Marktechpost

MAY 30, 2024

Introduction to AI and Machine Learning on Google Cloud This course introduces Google Cloud’s AI and ML offerings for predictive and generative projects, covering technologies, products, and tools across the data-to-AI lifecycle.

Artificial Intelligence 132

Artificial Intelligence Artificial Intelligence BERT Computer Vision 132

Towards AI

MAY 30, 2024

The broad range of topics covered with easy to understand examples will help any readers, and developers be in the know of the theory behind LLMs, prompt engineering, RAG, orchestration platforms and more. The defacto manual for AI Engineering. I highly recommend this book.” Seriously, pick it up.” Ahmed Moubtahij, ing.,

Prompt Engineering 109

Prompt Engineering Prompt Engineer LLM NLP 109

AWS Machine Learning Blog

NOVEMBER 29, 2023

Since launching in June 2023, the AWS Generative AI Innovation Center team of strategists, data scientists, machine learning (ML) engineers, and solutions architects have worked with hundreds of customers worldwide, and helped them ideate, prioritize, and build bespoke solutions that harness the power of generative AI.

Generative AI 112

Generative AI Prompt Engineer Prompt Engineering Machine Learning 112

AWS Machine Learning Blog

FEBRUARY 12, 2025

Machine learning (ML) engineers must make trade-offs and prioritize the most important factors for their specific use case and business requirements. For more information on application security, refer to Safeguard a generative AI travel agent with prompt engineering and Amazon Bedrock Guardrails.

Auto-classification 90

Auto-classification Generative AI Metadata Machine Learning 90

AWS Machine Learning Blog

MAY 30, 2024

Prompt engineering Prompt engineering is crucial for the knowledge retrieval system. The prompt guides the LLM on how to respond and interact based on the user question. Prompts also help ground the model.

Chatbots 130

Chatbots Prompt Engineer Prompt Engineering Large Language Models 130

Towards AI

SEPTEMBER 22, 2023

One example is prompt engineering. Prompt engineering has proved to be very useful. Some people foresaw the emergence of prompt engineer as a new title. Is this the future of the ML engineer? Let’s think about why prompt engineering has been developed.

Prompt Engineering 59

Prompt Engineering Prompt Engineer ML ML Engineer 59

AWS Machine Learning Blog

SEPTEMBER 1, 2023

After the completion of the research phase, the data scientists need to collaborate with ML engineers to create automations for building (ML pipelines) and deploying models into production using CI/CD pipelines. These users need strong end-to-end ML and data science expertise and knowledge of model deployment and inference.

Generative AI 127

Generative AI Prompt Engineer Prompt Engineering ML 127

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. ML engineers used to be crucial to AI projects because you needed to train custom models from scratch. Instead, Twain employs linguists and salespeople as prompt engineers.

Prompt Engineering 59

Prompt Engineering Prompt Engineer Generative AI Large Language Models 59

AWS Machine Learning Blog

MARCH 13, 2024

Use LLM prompt engineering to accommodate customized policies The pre-trained Toxicity Detection models from Amazon Transcribe and Amazon Comprehend provide a broad toxicity taxonomy, commonly used by social platforms for moderating user-generated content in audio and text formats. LLMs, in contrast, offer a high degree of flexibility.

Natural Language Processing 135

Natural Language Processing LLM Prompt Engineer Prompt Engineering 135

Towards AI

JANUARY 6, 2025

You may get hands-on experience in Generative AI, automation strategies, digital transformation, prompt engineering, etc. AI engineering professional certificate by IBM AI engineering professional certificate from IBM targets fundamentals of machine learning, deep learning, programming, computer vision, NLP, etc.

Artificial Intelligence 105

Artificial Intelligence Artificial Intelligence Computer Vision Deep Learning 105

Towards AI

JUNE 18, 2024

The principles of CNNs and early vision transformers are still important as a good background for ML engineers, even though they are much less popular nowadays. The book focuses on adapting large language models (LLMs) to specific use cases by leveraging Prompt Engineering, Fine-Tuning, and Retrieval Augmented Generation (RAG).

Large Language Models 80

Large Language Models Prompt Engineer Prompt Engineering LLM 80

Chatbots Life

MAY 12, 2023

We will discuss how models such as ChatGPT will affect the work of software engineers and ML engineers. Will ChatGPT replace software engineers? Will ChatGPT replace ML Engineers? Will ChatGPT replace ML Engineers? We will answer the question “ Will you lose your job?” And, as mentioned before.

ChatGPT 90

ChatGPT Software Engineer NLP ML Engineer 90

Towards AI

FEBRUARY 20, 2025

But who exactly is an LLM developer, and how are they different from software developers and ML engineers? Machine learning engineers specialize in training models from scratch and deploying them at scale. Well, briefly, software developers focus on building traditional applications using explicit code.

Neural Network 86

Neural Network Explainability LLM Software Development 86

AWS Machine Learning Blog

FEBRUARY 21, 2025

The concept of a compound AI system enables data scientists and ML engineers to design sophisticated generative AI systems consisting of multiple models and components. The following diagram compares predictive AI to generative AI.

LLM 89

LLM AI AI Data Scientist 89

Snorkel AI

MARCH 20, 2025

GenAI evaluation with SME-evaluator agreement AI/ML engineers develop specialized evaluators with ground truth. First, an AI/ML engineer is going to iterate on the prompt until LLM judgments match the ground truth provided by SMEs. This brings me to the third dimension, SME-evaluator agreement (or alignment).

ML Engineer 59

ML Engineer Automation Prompt Engineer Prompt Engineering 59

AWS Machine Learning Blog

JULY 24, 2024

You can customize the model using prompt engineering, Retrieval Augmented Generation (RAG), or fine-tuning. Fine-tuning an LLM can be a complex workflow for data scientists and machine learning (ML) engineers to operationalize. Each iteration can be considered a run within an experiment.

LLM 130

LLM ML Generative AI Machine Learning 130

AWS Machine Learning Blog

OCTOBER 4, 2023

Solution overview Amazon SageMaker is built on Amazon’s two decades of experience developing real-world ML applications, including product recommendations, personalization, intelligent shopping, robotics, and voice-assisted devices. In SageMaker Studio, choose the upload icon and upload the file to your SageMaker Studio instance.

LLM 118

LLM Large Language Models ML Data Scientist 118

TheSequence

NOVEMBER 12, 2023

📌 ML Engineering Event: Join Meta, PepsiCo, RiotGames, Uber & more at apply(ops) apply(ops) is in two days! PromptIDE Elon Musk’s xAI announced PromptIDE, a development environment for prompt engineering —> Read more. It’s what makes this market so fascinating.

OpenAI 64

OpenAI Generative AI ML Prompt Engineer 64

ODSC - Open Data Science

NOVEMBER 25, 2024

Some of our most popular in-person sessions at ODSC East were: Tackling Socioeconomic Bias in Machine Learning Managing the Volatility of AI Applications Building High-Quality Domain-Specific Models with Mergekit: A Cost-Effective Approach Using Small Language Models Simulating Ourselves and Our Societies With Generative Agents Synthetic Data for Anonymization, (..)

Data Science 52

Data Science AI Engineer Machine Learning Prompt Engineer 52

AWS Machine Learning Blog

APRIL 25, 2023

This allows ML engineers and admins to configure these environment variables so data scientists can focus on ML model building and iterate faster. AI/ML Specialist Solutions Architect at AWS, based in Virginia, US. SageMaker uses training jobs to launch this function as a managed job. Vikram Elango is a Sr.

Machine Learning 100

Machine Learning Data Scientist Python ML 100

Snorkel AI

MAY 4, 2023

AI development stack: AutoML, ML frameworks, no-code/low-code development. Join us on June 7-8 to learn how to use your data to build your AI moat at The Future of Data-Centric AI 2023. The free virtual conference is the largest annual gathering of the data-centric AI community.

Computer Vision 52

Computer Vision Large Language Models Natural Language Processing AI 52

Snorkel AI

MAY 4, 2023

AI development stack: AutoML, ML frameworks, no-code/low-code development. Join us on June 7-8 to learn how to use your data to build your AI moat at The Future of Data-Centric AI 2023. The free virtual conference is the largest annual gathering of the data-centric AI community.

Computer Vision 52

Computer Vision Large Language Models Natural Language Processing AI 52

Heartbeat

OCTOBER 5, 2023

Feature Engineering and Model Experimentation MLOps: Involves improving ML performance through experiments and feature engineering. LLMOps: LLMs excel at learning from raw data, making feature engineering less relevant. The focus shifts towards prompt engineering and fine-tuning.

Large Language Models 52

Large Language Models DevOps Machine Learning Prompt Engineer 52

AWS Machine Learning Blog

MARCH 1, 2023

This blog post details the implementation of generative AI-assisted fashion online styling using text prompts. Machine learning (ML) engineers can fine-tune and deploy text-to-semantic-segmentation and in-painting models based on pre-trained CLIPSeq and Stable Diffusion with Amazon SageMaker.

Generative AI 103

Generative AI AI AI Auto-classification 103

AWS Machine Learning Blog

MAY 9, 2024

AI/ML Specialist Solutions Architect at AWS, based in Virginia, US. He is currently focused on generative AI, LLMs, prompt engineering, large model inference optimization, and scaling ML across enterprises. Vikram Elango is a Sr.

ML 132

ML Generative AI AI AI 132

ODSC - Open Data Science

JANUARY 10, 2024

Using Graphs for Large Feature Engineering Pipelines Wes Madrigal | ML Engineer | Mad Consulting This talk will outline the complexity of feature engineering from raw entity-level data, the reduction in complexity that comes with composable compute graphs, and an example of the working solution.

Large Language Models 52

Large Language Models Deep Learning Data Science LLM 52

Heartbeat

JULY 17, 2023

Comet allows ML engineers to track these metrics in real-time and visualize their performance using interactive dashboards. Evaluation Metrics Choosing the right evaluation metrics for a classification task is critical to accurately benchmark the performance of computer vision models. What comes out is amazing AI-generated art!

Computer Vision 52

Computer Vision Auto-classification Deep Learning Machine Learning 52

Snorkel AI

JUNE 9, 2023

Among other topics, he highlighted how visual prompts and parameter-efficient models enable rapid iteration for improved data quality and model performance. He also described a near future where large companies will augment the performance of their finance and tax professionals with large language models, co-pilots, and AI agents.

Large Language Models 52

Large Language Models Data Scientist Machine Learning Computer Vision 52

Snorkel AI

JUNE 9, 2023

Among other topics, he highlighted how visual prompts and parameter-efficient models enable rapid iteration for improved data quality and model performance. He also described a near future where large companies will augment the performance of their finance and tax professionals with large language models, co-pilots, and AI agents.

Large Language Models 52

Large Language Models Data Scientist Machine Learning Computer Vision 52

The MLOps Blog

JUNE 27, 2023

The platform also offers features for hyperparameter optimization, automating model training workflows, model management, prompt engineering, and no-code ML app development. Valohai Valohai provides a collaborative environment for managing and automating machine learning projects.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

ODSC - Open Data Science

JANUARY 3, 2025

In this hands-on session, attendees will learn practical techniques like model testing across diverse scenarios, prompt engineering , hyperparameter optimization , fine-tuning , and benchmarking models in sandbox environments. Cloning NotebookLM with Open Weights Models Niels Bantilan, Chief ML Engineer atUnion.AI

LLM 40

LLM AI AI Prompt Engineer 40

The MLOps Blog

AUGUST 3, 2023

This is Piotr Niedźwiedź and Aurimas Griciūnas from neptune.ai , and you’re listening to ML Platform Podcast. Stefan is a software engineer, data scientist, and has been doing work as an ML engineer. We have someone precisely using it more for feature engineering, but using it within a Flask app.

ML 52

ML Data Scientist Software Engineer Machine Learning 52

AWS Machine Learning Blog

JANUARY 26, 2024

The goal of this post is to empower AI and machine learning (ML) engineers, data scientists, solutions architects, security teams, and other stakeholders to have a common mental model and framework to apply security best practices, allowing AI/ML teams to move fast without trading off security for speed.

Generative AI 138

Generative AI ML LLM AI 138

AWS Machine Learning Blog

NOVEMBER 29, 2023

Data scientists collaborate with ML engineers to transition code from notebooks to repositories, creating ML pipelines using Amazon SageMaker Pipelines, which connect various processing steps and tasks, including pre-processing, training, evaluation, and post-processing, all while continually incorporating new production data.

LLM 114

LLM Data Scientist Algorithm Generative AI 114

AWS Machine Learning Blog

DECEMBER 17, 2024

Amazon SageMaker helps data scientists and machine learning (ML) engineers build FMs from scratch, evaluate and customize FMs with advanced techniques, and deploy FMs with fine-grain controls for generative AI use cases that have stringent requirements on accuracy, latency, and cost. Of the six challenges, the LLM met only one.

LLM 99

LLM Prompt Engineer Prompt Engineering Generative AI 99

Marktechpost

NOVEMBER 14, 2024

That’s why we provide an end-to-end platform backed by a dedicated team of ML engineers to help you every step of the way. Right now, what I hear from organizations is that when they move to production, they can often get a model to 70% accuracy with prompt engineering alone.

Neural Network 131

Neural Network Deep Learning Machine Learning Generative AI 131

Marktechpost

APRIL 10, 2025

Bio: Hamza Tahir is a software developer turned ML engineer. Based on his learnings from deploying ML in production for predictive maintenance use-cases in his previous startup, he co-created ZenML , an open-source MLOps framework for creating production grade ML pipelines on any infrastructure stack.

Software Engineer 49

Software Engineer LLM ML Prompt Engineer 49