Towards AI

JANUARY 6, 2025

Artificial Intelligence graduate certificate by STANFORD SCHOOL OF ENGINEERING Artificial Intelligence graduate certificate; taught by Andrew Ng, and other eminent AI prodigies; is a popular course that dives deep into the principles and methodologies of AI and related fields.

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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.

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AWS Machine Learning Blog

FEBRUARY 26, 2024

Large Language Models (LLMs) have revolutionized the field of natural language processing (NLP), improving tasks such as language translation, text summarization, and sentiment analysis. Rushabh Lokhande is a Senior Data & ML Engineer with AWS Professional Services Analytics Practice.

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AWS Machine Learning Blog

FEBRUARY 28, 2024

This generative AI task is called text-to-SQL, which generates SQL queries from natural language processing (NLP) and converts text into semantically correct SQL. The solution in this post aims to bring enterprise analytics operations to the next level by shortening the path to your data using natural language.

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Metadata Generative AI LLM NLP 127

AWS Machine Learning Blog

MARCH 13, 2024

The traditional method of training an in-house classification model involves cumbersome processes such as data annotation, training, testing, and model deployment, requiring the expertise of data scientists and ML engineers. LLMs, in contrast, offer a high degree of flexibility.

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Natural Language Processing LLM Prompt Engineer Prompt Engineering 127

Chatbots Life

MAY 16, 2023

Services : AI Solution Development, ML Engineering, Data Science Consulting, NLP, AI Model Development, AI Strategic Consulting, Computer Vision. Data Monsters can help companies deploy, train and test machine learning pipelines for natural language processing and computer vision.

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AWS Machine Learning Blog

DECEMBER 14, 2023

For further insights into how Talent.com and AWS collaboratively built cutting-edge natural language processing and deep learning model training techniques, utilizing Amazon SageMaker to craft a job recommendation system, refer to From text to dream job: Building an NLP-based job recommender at Talent.com with Amazon SageMaker.

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ETL Data Scientist Machine Learning Deep Learning 100

AWS Machine Learning Blog

JANUARY 25, 2023

Amazon SageMaker Clarify is a feature of Amazon SageMaker that enables data scientists and ML engineers to explain the predictions of their ML models. In this post, we illustrate the use of Clarify for explaining NLP models. Configure Clarify Clarify NLP is compatible with regression and classification models.

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Explainability Algorithm Natural Language Processing Machine Learning 81

Chatbots Life

MAY 12, 2023

As everything is explained from scratch but extensively I hope you will find it interesting whether you are NLP Expert or just want to know what all the fuss is about. We will discuss how models such as ChatGPT will affect the work of software engineers and ML engineers. Will ChatGPT replace software engineers?

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AWS Machine Learning Blog

APRIL 29, 2024

Historically, natural language processing (NLP) would be a primary research and development expense. In 2024, however, organizations are using large language models (LLMs), which require relatively little focus on NLP, shifting research and development from modeling to the infrastructure needed to support LLM workflows.

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ML Python Data Scientist Machine Learning 118

AWS Machine Learning Blog

MARCH 14, 2024

Amazon Kendra uses natural language processing (NLP) to understand user queries and find the most relevant documents. Grace Lang is an Associate Data & ML engineer with AWS Professional Services. To enable quick information retrieval, we use Amazon Kendra as the index for these documents.

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AWS Machine Learning Blog

MAY 13, 2024

Evaluating LLMs is an undervalued part of the machine learning (ML) pipeline. We benchmark the results with a metric used for evaluating summarization tasks in the field of natural language processing (NLP) called Recall-Oriented Understudy for Gisting Evaluation (ROUGE).

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Generative AI Prompt Engineering Prompt Engineer LLM 125

AWS Machine Learning Blog

JULY 24, 2024

Large language models (LLMs) have achieved remarkable success in various natural language processing (NLP) tasks, but they may not always generalize well to specific domains or tasks. You can customize the model using prompt engineering, Retrieval Augmented Generation (RAG), or fine-tuning.

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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. His area of research is all things natural language (like NLP, NLU, and NLG). The following diagram compares predictive AI to generative AI.

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LLM AI AI Data Scientist 79

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.

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Data Scientist Machine Learning Big Data Algorithm 52

AWS Machine Learning Blog

AUGUST 16, 2023

Thomson Reuters Labs, the company’s dedicated innovation team, has been integral to its pioneering work in AI and natural language processing (NLP). A key milestone was the launch of Westlaw Is Natural (WIN) in 1992. Outside of his professional life, he enjoys working on cars and photography.

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AWS Machine Learning Blog

OCTOBER 19, 2023

Amazon Comprehend is a natural language processing (NLP) service that uses ML to uncover insights and relationships in unstructured data, with no managing infrastructure or ML experience required. The following diagram illustrates the SageMaker MLOps workflow.

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Snorkel AI

MAY 4, 2023

Large Language Models (LLMs) such as GPT-4 and LLaMA have revolutionized natural language processing and understanding, enabling a wide range of applications, from conversational AI to advanced text generation. Enterprise use cases: predictive AI, generative AI, NLP, computer vision, conversational AI.

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Computer Vision Large Language Models Natural Language Processing AI 52

Snorkel AI

MAY 4, 2023

Large Language Models (LLMs) such as GPT-4 and LLaMA have revolutionized natural language processing and understanding, enabling a wide range of applications, from conversational AI to advanced text generation. Enterprise use cases: predictive AI, generative AI, NLP, computer vision, conversational AI.

Computer Vision 52

Computer Vision Large Language Models Natural Language Processing AI 52

AWS Machine Learning Blog

SEPTEMBER 23, 2024

Throughout this exercise, you use Amazon Q Developer in SageMaker Studio for various stages of the development lifecycle and experience firsthand how this natural language assistant can help even the most experienced data scientists or ML engineers streamline the development process and accelerate time-to-value.

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ML Computer Vision Data Scientist Machine Learning 80

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. Security SMEs review the architecture based on business security policies and needs.

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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.

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Machine Learning Data Drift Data Science Data Scientist 52

Snorkel AI

JUNE 9, 2023

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. She highlighted how the platform enables businesses to adapt LLMs to customer-specific data and incorporate domain knowledge.

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Large Language Models Data Scientist Machine Learning Computer Vision 52

Snorkel AI

JUNE 9, 2023

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. She highlighted how the platform enables businesses to adapt LLMs to customer-specific data and incorporate domain knowledge.

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Large Language Models Data Scientist Machine Learning Computer Vision 52

AWS Machine Learning Blog

JUNE 8, 2023

This enables you to begin machine learning (ML) quickly. It performs well on various natural language processing (NLP) tasks, including text generation. A SageMaker real-time inference endpoint enables fast, scalable deployment of ML models for predicting events.

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Snorkel AI

OCTOBER 12, 2023

The center aimed to address recurring bottlenecks in their ML projects and improve collaborative workflows between data scientists and subject-matter experts. In this presentation, center NLP Engineer James Dunham shares takeaways from the half-dozen project teams who used Snorkel in the past year.

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Data Scientist ML Computer Vision AI 64

AWS Machine Learning Blog

AUGUST 1, 2023

Flan-T5 XL is a powerful and versatile model designed for a wide range of language tasks. By fine-tuning the model with your domain-specific data, you can optimize its performance for your particular use case, such as text summarization or any other NLP task. No ML engineering experience required. It’s as easy as that!

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ML Large Language Models NLP Machine Learning 85

Heartbeat

OCTOBER 5, 2023

The emergence of Large Language Models (LLMs) like OpenAI's GPT , Meta's Llama , and Google's BERT has ushered in a new era in this field. These LLMs can generate human-like text, understand context, and perform various Natural Language Processing (NLP) tasks.

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Large Language Models DevOps Machine Learning Prompt Engineer 52

Snorkel AI

OCTOBER 12, 2023

The center aimed to address recurring bottlenecks in their ML projects and improve collaborative workflows between data scientists and subject-matter experts. In this presentation, center NLP Engineer James Dunham shares takeaways from the half-dozen project teams who used Snorkel in the past year.

Data Scientist 59

Data Scientist ML Computer Vision AI 59

Snorkel AI

OCTOBER 12, 2023

The center aimed to address recurring bottlenecks in their ML projects and improve collaborative workflows between data scientists and subject-matter experts. In this presentation, center NLP Engineer James Dunham shares takeaways from the half-dozen project teams who used Snorkel in the past year.

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Data Scientist NLP ML Computer Vision 52

The MLOps Blog

JULY 18, 2023

In terms of the team set-up, does the team sort of leverage language experts in some sense, or how do you leverage language experts? And even on the operation side of things, is there a separate operations team, and then you have your research or ml engineers doing these pipelines and stuff? Not all, but some.

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Conversational AI Natural Language Processing Machine Learning AI 52

The MLOps Blog

MAY 10, 2023

2 For dynamic models, such as those with variable-length inputs or outputs, which are frequent in natural language processing (NLP) and computer vision, PyTorch offers improved support. This allows for more flexibility in modifying the model during training or inference. In this example, I’ll use the Neptune.

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Python Metadata ML Machine Learning 105

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.

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The MLOps Blog

AUGUST 11, 2023

At that point, the Data Scientists or ML Engineers become curious and start looking for such implementations. Advantages and disadvantages of embeddings design pattern The advantages of the embedding method of data representation in machine learning pipelines lie in its applicability to several ML tasks and ML pipeline components.

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ML Machine Learning Data Ingestion Deep Learning 52

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.

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Machine Learning Data Scientist ML Metadata 69

Mlearning.ai

MAY 3, 2023

The built APP provides an easy web interface to access the large language models with several built-in application utilities for direct use, significantly lowering the barrier for the practitioners to use the LLM’s Natural Language Processing (NLP) capabilities in an amateur way focusing on their specific use cases.

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Large Language Models Python Auto-complete Natural Language Processing 52

Snorkel AI

MAY 24, 2023

Gideon Mann is the head of the ML Product and Research team in the Office of the CTO at Bloomberg LP. He leads corporate strategy for machine learning, natural language processing, information retrieval, and alternative data. He has over 30 publications and more than 20 patents in machine learning and NLP.

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Machine Learning Data Scientist Computer Vision ML 52