KDnuggets

NOVEMBER 7, 2019

In this tutorial, we show how to apply mathematical set operations (union, intersection, and difference) to Pandas DataFrames with the goal of easing the task of comparing the rows of two datasets.

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Data Preparation Python Data Science 300

AWS Machine Learning Blog

SEPTEMBER 14, 2023

“Data locked away in text, audio, social media, and other unstructured sources can be a competitive advantage for firms that figure out how to use it“ Only 18% of organizations in a 2019 survey by Deloitte reported being able to take advantage of unstructured data. The majority of data, between 80% and 90%, is unstructured data.

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Kaggle

JULY 29, 2020

[link] David Mezzetti is the founder of NeuML, a data analytics and machine learning company that develops innovative products backed by machine learning. He previously co-founded and built Data Works into a 50+ person well-respected software services company. All of the notebooks are in Python.

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ETL Data Scientist Machine Learning Machine Learning 71

AWS Machine Learning Blog

DECEMBER 18, 2024

Fastweb , one of Italys leading telecommunications operators, recognized the immense potential of AI technologies early on and began investing in this area in 2019. With a vision to build a large language model (LLM) trained on Italian data, Fastweb embarked on a journey to make this powerful AI capability available to third parties.

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Clustering AWS AI AI 74

AWS Machine Learning Blog

MARCH 28, 2024

LangChain is an open source Python library designed to build applications with LLMs. Data preparation In this post, we use several years of Amazon’s Letters to Shareholders as a text corpus to perform QnA on. For more detailed steps to prepare the data, refer to the GitHub repo.

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The MLOps Blog

APRIL 5, 2023

The platform can assign specific roles to team members involved in the packaging process and grant them access to relevant aspects such as data preparation, training, deployment, and monitoring. How to Save and Reuse Your Machine Learning Models with Python Machine Learning Mastery. References Géron, A. Brownlee, J.

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ML ML Machine Learning Machine Learning 69

AWS Machine Learning Blog

SEPTEMBER 11, 2024

In terms of resulting speedups, the approximate order is programming hardware, then programming against PBA APIs, then programming in an unmanaged language such as C++, then a managed language such as Python. The CUDA platform is used through complier directives and extensions to standard languages, such as the Python cuNumeric library.

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AWS Machine Learning Blog

JULY 29, 2024

Launched in August 2019, Forecast predates Amazon SageMaker Canvas , a popular low-code no-code AWS tool for building, customizing, and deploying ML models, including time series forecasting models. Python script – Use a Python script to merge the datasets.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

Q might answer with something like, “This application is building a basic support ticket system using Python Flask and AWS Lambda” and go on to describe each of its core capabilities, how they are implemented, and much more).

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AWS Machine Learning Blog

NOVEMBER 11, 2024

We then also cover how to fine-tune the model using SageMaker Python SDK. FMs through SageMaker JumpStart in the SageMaker Studio UI and the SageMaker Python SDK. Fine-tune using the SageMaker Python SDK You can also fine-tune Meta Llama 3.2 models using the SageMaker Python SDK. You can access the Meta Llama 3.2

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