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. Refer to the Python documentation for an example. The function sends that average to CloudWatch metrics.

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Large Language Models LLM Big Data Machine Learning 120

AWS Machine Learning Blog

DECEMBER 14, 2023

Our pipeline belongs to the general ETL (extract, transform, and load) process family that combines data from multiple sources into a large, central repository. The system includes feature engineering, deep learning model architecture design, hyperparameter optimization, and model evaluation, where all modules are run using Python.

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ETL Data Scientist Machine Learning Deep Learning 93

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. Custom transforms allow you to run your own Python or SQL code within a Data Wrangler flow.

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Machine Learning Python ML Automation 99

AWS Machine Learning Blog

FEBRUARY 28, 2024

Structured Query Language (SQL) is a complex language that requires an understanding of databases and metadata. 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. Set up the SDK for Python (Boto3).

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Metadata LLM Generative AI NLP 117

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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LLM ML Generative AI Machine Learning 116

AWS Machine Learning Blog

JUNE 23, 2023

FastAPI is a modern, high-performance web framework for building APIs with Python. It stands out when it comes to developing serverless applications with RESTful microservices and use cases requiring ML inference at scale across multiple industries. Log in to your account and choose the Region where you want to deploy the solution.

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Large Language Models ML Python Machine Learning 89

Pickl AI

NOVEMBER 28, 2024

Summary: The blog discusses essential skills for Machine Learning Engineer, emphasising the importance of programming, mathematics, and algorithm knowledge. Key programming languages include Python and R, while mathematical concepts like linear algebra and calculus are crucial for model optimisation. during the forecast period.

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Machine Learning Neural Network ML Engineer Algorithm 52

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. We use the SageMaker Python SDK for this purpose. Clarify supports 62 languages and can handle text with multiple languages.

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Explainability Natural Language Processing Algorithm Machine Learning 71

The MLOps Blog

JUNE 27, 2023

Knowledge and skills in the organization Evaluate the level of expertise and experience of your ML team and choose a tool that matches their skill set and learning curve. For example, if your team is proficient in Python and R, you may want an MLOps tool that supports open data formats like Parquet, JSON, CSV, etc.,

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Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

DECEMBER 13, 2023

ML operations, known as MLOps, focus on streamlining, automating, and monitoring ML models throughout their lifecycle. Data scientists, ML engineers, IT staff, and DevOps teams must work together to operationalize models from research to deployment and maintenance.

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ML Automation Metadata Software Development 112

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 Engineer Prompt Engineering LLM 116

Pickl AI

JANUARY 29, 2024

AI comprises Natural Language Processing, computer vision, and robotics. ML focuses on algorithms like decision trees, neural networks, and support vector machines for pattern recognition. Skills Proficiency in programming languages (Python, R), statistical analysis, and domain expertise are crucial.

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Data Science ML Machine Learning Artificial Intelligence 52

AWS Machine Learning Blog

OCTOBER 23, 2023

Given this mission, Talent.com and AWS joined forces to create a job recommendation engine using state-of-the-art natural language processing (NLP) and deep learning model training techniques with Amazon SageMaker to provide an unrivaled experience for job seekers. The recommendation system has driven an 8.6%

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NLP Deep Learning Machine Learning Natural Language Processing 101

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 74

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

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? We can ask the model to generate a python function or a recipe for a cheesecake. Will ChatGPT replace ML Engineers?

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ChatGPT Software Engineer NLP Prompt Engineer 90

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. This is your Custom Python Hook speaking!"

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Generative AI LLM Machine Learning Large Language Models 73

AWS Machine Learning Blog

AUGUST 1, 2023

Jurassic-2 Grande Instruct is a large language model (LLM) by AI21 Labs, optimized for natural language instructions and applicable to various language tasks. It offers an easy-to-use API and Python SDK, balancing quality and affordability. No ML engineering experience required. It’s as easy as that!

ML 74

ML Large Language Models NLP Machine Learning 74

Snorkel AI

OCTOBER 12, 2023

Leveraging Foundation Models and LLMs for Enterprise-Grade NLP In recent years, large language models (LLMs) have shown tremendous potential in solving natural language processing (NLP) problems. She starts by discussing the challenges associated with extracting from PDFs and other semi-structured documents.

Data Scientist 64

Data Scientist ML Computer Vision AI 64

Snorkel AI

OCTOBER 12, 2023

Leveraging Foundation Models and LLMs for Enterprise-Grade NLP In recent years, large language models (LLMs) have shown tremendous potential in solving natural language processing (NLP) problems. She starts by discussing the challenges associated with extracting from PDFs and other semi-structured documents.

Data Scientist 59

Data Scientist ML Computer Vision AI 59

Snorkel AI

OCTOBER 12, 2023

Leveraging Foundation Models and LLMs for Enterprise-Grade NLP In recent years, large language models (LLMs) have shown tremendous potential in solving natural language processing (NLP) problems. She starts by discussing the challenges associated with extracting from PDFs and other semi-structured documents.

Data Scientist 52

Data Scientist NLP AI AI 52

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 Deep Learning 111

Mlearning.ai

MAY 3, 2023

An open-source, low-code Python wrapper for easy usage of the Large Language Models such as ChatGPT, AutoGPT, LLaMa, GPT-J, and GPT4All An introduction to “ pychatgpt_gui” —  A GUI-based APP for LLM’s with custom-data training and pre-trained inferences. It is an open-source python package.

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Large Language Models Python Auto-complete Natural Language Processing 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

AWS Machine Learning Blog

OCTOBER 11, 2024

data # Assing local directory path to a python variable local_data_path = "./data/" data/" # Assign S3 bucket name to a python variable. Ginni Malik is a Senior Data & ML Engineer with AWS Professional Services. This was created in Step-2 above. Satish Sarapuri is a Sr.

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Metadata Generative AI LLM Data Ingestion 92