AWS Machine Learning Blog

SEPTEMBER 11, 2024

These activities cover disparate fields such as basic data processing, analytics, and machine learning (ML). ML is often associated with PBAs, so we start this post with an illustrative figure. The ML paradigm is learning followed by inference. The union of advances in hardware and ML has led us to the current day.

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AWS ML ML Clustering 113

Flipboard

NOVEMBER 24, 2023

This use case highlights how large language models (LLMs) are able to become a translator between human languages (English, Spanish, Arabic, and more) and machine interpretable languages (Python, Java, Scala, SQL, and so on) along with sophisticated internal reasoning. Clay Elmore is an AI/ML Specialist Solutions Architect at AWS.

Database 159

Database AWS ETL SQL 159

Towards AI

JULY 21, 2023

The cryptic book arrived on the internet in the mid 2010’s by the now wildly popular but mysterious internet group 3301. Instead of building a model from… github.com NERtwork Awesome new shell/python script that graphs a network of co-occurring entities from plain text!

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Natural Language Processing ML ML Python 98

AWS Machine Learning Blog

DECEMBER 6, 2023

Overview of RAG RAG solutions are inspired by representation learning and semantic search ideas that have been gradually adopted in ranking problems (for example, recommendation and search) and natural language processing (NLP) tasks since 2010. We use the following Python script to recreate tables as pandas DataFrames.

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SQL AWS Analytics Analytics 126

AWS Machine Learning Blog

SEPTEMBER 27, 2024

Let’s analyze the initial CloudFormation template: AWSTemplateFormatVersion: '2010-09-09' Description: > This CloudFormation stack sets up a serverless data processing pipeline triggered by file uploads to an S3 bucket. The step-by-step explanation is augmented with few-shot learning examples to develop an initial CloudFormation template.

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AWS AI AI Computer Science 123

Towards AI

JULY 21, 2023

The Continuing Story of Neural Magic Around New Year’s time, I pondered about the upcoming sparsity adoption and its consequences on inference w/r/t ML models. Their infrastructure is built on top of FastAPI and supports Python, Go and Ruby languages. and share with friends! The company is Neural Magic. You can read their blog post ?

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Natural Language Processing Azure Python Artificial Intelligence 52

Mlearning.ai

JULY 20, 2023

In this three-part blog series, we delve into the basics of probability and conditional probability, using the engaging context of cycling and supplemented by dynamic Python simulations. The Python code snippet provided below supports this analysis by performing the following steps: · It loads the weather station inventory.

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Python Algorithm Machine Learning Machine Learning 52

Mlearning.ai

JUNE 18, 2023

While Google Colab’s main focus is running Python code using Jupyter notebooks, with magic commands non-Python code can also be executed. This opens up plenty of opportunities, as many AI models are not written in Python. We will use Python to help us do this. which is accessible from Google Colab.

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Deep Learning Deep Learning Python ML 52

Mlearning.ai

JANUARY 31, 2023

In particular, my code is based on rospy, which, as you might guess, is a python package allowing you to write code to interact with ROS. More broadly, I think switching from python to C++ could make a huge difference. 2010, doi: 10.1109/TBME.2010.2060723. I made some attempts to improve this, really with no significant gain.

Clustering 52

Clustering Algorithm Machine Learning Machine Learning 52

O'Reilly Media

JULY 25, 2023

For instance, problems like “write a Python function that takes a list of names, splits them by first and last name, and sorts by last name.” It’s well-known that current AI tools can solve these kinds of problems even better than many students can. This choice also inspired me to call my project Swift Papers.

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AI AI ML ML 98

AWS Machine Learning Blog

NOVEMBER 26, 2024

We add the following to the end of the prompt: provide the response in json format with the key as “class” and the value as the class of the document We get the following response: { "class": "ID" } You can now read the JSON response using a library of your choice, such as the Python JSON library. The following image is of a gearbox.

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ML ML AI AI 106