ODSC - Open Data Science

MAY 22, 2023

Training AI-Powered Algorithmic Trading with Python Dr. Yves J. Hilpisch | The AI Quant | CEO The Python Quants & The AI Machine, Adjunct Professor of Computational Finance This session will cover the essential Python topics and skills that will enable you to apply AI and Machine Learning (ML) to Algorithmic Trading.

Data Science 97

Data Science Machine Learning Machine Learning Python 97

Data Science Dojo

JULY 17, 2023

It is used for machine learning, natural language processing, and computer vision tasks. It is similar to TensorFlow, but it is designed to be more Pythonic. For example, PyTorch was used by OpenAI to develop its GPT-3 language model. Scikit-learn Scikit-learn is an open-source machine learning library for Python.

Data Analysis 195

Data Analysis Data Analysis Tableau Machine Learning 195

Towards AI

JULY 21, 2023

Photo by Kunal Shinde on Unsplash NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER NLP News Cypher | 08.09.20 Where are those commonsense reasoning demos? Research Work on methods that address the challenges of low-resource languages. Forge Where are we? What is the state of NLP? So… where are we….

Natural Language Processing 98

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Flipboard

APRIL 24, 2025

This can be implemented using natural language processing (NLP) or LLMs to apply named entity recognition (NER) capabilities to drive the resolution process. This optional step has the most value when there are many named resources and the lookup process is complex.

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AWS Machine Learning Blog

JANUARY 31, 2024

Embeddings play a key role in natural language processing (NLP) and machine learning (ML). Text embedding refers to the process of transforming text into numerical representations that reside in a high-dimensional vector space. client( service_name='bedrock', region_name='us-west-2', ) bedrock_runtime = boto3.client(

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phData

NOVEMBER 28, 2024

Text splitting is breaking down a long document or text into smaller, manageable segments or “chunks” for processing. This is widely used in Natural Language Processing (NLP), where it plays a pivotal role in pre-processing unstructured textual data. The below flow diagram illustrates this process.

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Python Database SQL Machine Learning 52

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. The code below illustrates the same.

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AWS Machine Learning Blog

NOVEMBER 7, 2023

Today, we are excited to unveil three generative AI demos, licensed under MIT-0 license : Amazon Kendra with foundational LLM – Utilizes the deep search capabilities of Amazon Kendra combined with the expansive knowledge of LLMs. Having the right setup in place is the first step towards a seamless deployment of the demos. Python 3.6

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AWS Machine Learning Blog

APRIL 19, 2023

The DJL is a deep learning framework built from the ground up to support users of Java and JVM languages like Scala, Kotlin, and Clojure. Our data scientists train the model in Python using tools like PyTorch and save the model as PyTorch scripts. For this reason, many DJL users also use it for inference only. With v0.21.0

ML 98

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AWS Machine Learning Blog

SEPTEMBER 1, 2023

We use Streamlit for the sample demo application UI. For all the supported parameters, refer to Streaming Python configuration. Because it’s part of the common data formats supported for inference , we can use the default deserializer provided by the SageMaker Python SDK to deserialize the JSON lines data.

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Chatbots Life

MARCH 17, 2023

That too in a language that is simple and easy for us to comprehend. This is where Natural Language Processing (NLP) makes its entrance. Natural language — the language that humans use to communicate with each other. Python, Java, C++, C, etc., are all examples of programming languages.

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AWS Machine Learning Blog

DECEMBER 14, 2023

Amazon Comprehend is a natural-language processing (NLP) service that provides pre-trained and custom APIs to derive insights from textual data. For the demo, we use simulated bank statements like the following example. To start the state machine, run the following Python code: import boto3 stepfunctions_client = boto3.client('stepfunctions')

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AWS Machine Learning Blog

AUGUST 30, 2023

T5 reframes natural language processing (NLP) tasks into a unified text-to-text-format, in contrast to BERT -style models that can only output either a class label or a span of the input. medium 2vCPU+4GiB notebook instance with a Python 3 kernel. We use an ml.t3.medium pip install nest-asyncio==1.5.5 --quiet !pip

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AWS Machine Learning Blog

APRIL 3, 2023

We also demonstrate how you can engineer prompts for Flan-T5 models to perform various natural language processing (NLP) tasks. Task Prompt (template in bold) Model output Summarization Briefly summarize this paragraph: Amazon Comprehend uses natural language processing (NLP) to extract insights about the content of documents.

Natural Language Processing 101

Natural Language Processing Machine Learning Machine Learning Algorithm 101

Towards AI

JULY 21, 2023

Photo by adrianna geo on Unsplash NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER NLP News Cypher | 08.23.20 A toolkit that allows the developer to dig deep into language models, in addition to dataset visualization. I tend to view LIT as an ML demo on steroids for prototyping. Fury What a week.

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Towards AI

JULY 21, 2023

Photo by Will Truettner on Unsplash NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER NLP News Cypher | 07.26.20 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! The demo is for building/training an NER LSTM model.

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DrivenData Labs

DECEMBER 10, 2023

Currently, published research may be spread across a variety of different publishers, including free and open-source ones like those used in many of this challenge's demos (e.g. He also boasts several years of experience with Natural Language Processing (NLP). On the server side, we opted for Python.

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Google Research AI blog

NOVEMBER 2, 2022

To explore this possibility, we developed Code as Policies (CaP), a robot-centric formulation of language model-generated programs executed on physical systems. CaP extends our prior work , PaLM-SayCan , by enabling language models to complete even more complex robotic tasks with the full expression of general-purpose Python code.

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AWS Machine Learning Blog

JANUARY 29, 2025

Watch this video demo for a step-by-step guide. You can customize the retry behavior using the AWS SDK for Python (Boto3) Config object. Once you are ready to import the model, use this step-by-step video demo to help you get started. The restoration time varies depending on the on-demand fleet size and model size.

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AWS Machine Learning Blog

APRIL 7, 2023

Retailers can deliver more frictionless experiences on the go with natural language processing (NLP), real-time recommendation systems, and fraud detection. Note that this integration is only available in us-east-1 and us-west-2 , and you will be using us-east-1 for the duration of the demo. Choose Manage.

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Heartbeat

JUNE 5, 2023

PyTorch For tasks like computer vision and natural language processing, Using the Torch library as its foundation, PyTorch is a free and open-source machine learning framework that comes in handy. Anomalib Anomalib is a Python library that helps users to detect anomalies in time-series data.

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AWS Machine Learning Blog

JANUARY 25, 2023

In this post, we provide an overview of how to deploy and run inference with the Stable Diffusion upscaler model in two ways: via JumpStart’s user interface (UI) in Amazon SageMaker Studio , and programmatically through JumpStart APIs available in the SageMaker Python SDK. The following examples contain code snippets.

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AWS Machine Learning Blog

FEBRUARY 14, 2023

For the purposes of the demo, you will have two different users in Amazon Cognito belonging to two different departments. At a high level, you need to perform the following steps to enable this demo: Set up an S3 bucket data source with the appropriate documents and folder structure. sessionAttributes”.”idtokenjwt” slot name”.”value”.”interpretedValue”

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AWS Machine Learning Blog

JANUARY 17, 2023

In this solution, we train and deploy a churn prediction model that uses a state-of-the-art natural language processing (NLP) model to find useful signals in text. When running this notebook on Studio, you should make sure the Python 3 (PyTorch 1.10 Demo notebook. CPU Optimized) image/kernel is used.

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ODSC - Open Data Science

FEBRUARY 14, 2023

Since its release on November 30, 2022 by OpenAI , the ChatGPT public demo has taken the world by storm. It is the latest in the research lab’s lineage of large language models using Generative Pre-trained Transformer (GPT) technology. Like its predecessors, ChatGPT generates text in a variety of styles, for a variety of purposes.

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Explosion

OCTOBER 22, 2016

This is a guest post by Wah Loon Keng , the author of spacy-nlp , a client that exposes spaCy ’s NLP text parsing to Node.js (and other languages) via Socket.IO. Natural Language Processing and other AI technologies promise to let us build applications that offer smarter, more context-aware user experiences.

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Python Database Natural Language Processing AI 52

Mlearning.ai

FEBRUARY 9, 2023

If you’re in the field of Natural Language Processing, you’ve probably heard about Hugging Face. Hugging Face is a library that provides pre-trained language models for NLP tasks such as text classification, sentiment analysis, and more. Hugging Face Hub is a platform with models, datasets, and demo applications.

Deep Learning 52

Deep Learning Deep Learning Natural Language Processing Machine Learning 52

AWS Machine Learning Blog

MARCH 19, 2024

Generative language models have proven remarkably skillful at solving logical and analytical natural language processing (NLP) tasks. We demonstrate the approach using batch inference on Amazon Bedrock: We access the Amazon Bedrock Python SDK in JupyterLab on an Amazon SageMaker notebook instance. whl | head -1) !pip

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AWS Machine Learning Blog

MAY 22, 2023

Fine-tune FLAN-T5 using a Python notebook Our example notebook shows how to use Jumpstart and SageMaker to programmatically fine-tune and deploy a FLAN T5 XL model. It develops insights by recognizing the entities, key phrases, language, sentiments, and other common elements in a document. It can be run in Studio or locally.

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AWS Machine Learning Blog

MAY 13, 2024

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). Evaluating LLMs is an undervalued part of the machine learning (ML) pipeline. It is time-consuming but, at the same time, critical.

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AWS Machine Learning Blog

NOVEMBER 17, 2023

The following code snippet demonstrates how to call the Amazon Rekognition DetectModerationLabel API to moderate images within an AWS Lambda function using the Python Boto3 library: import boto3 # Initialize the Amazon Rekognition client object rekognition = boto3.client('rekognition') The following diagram illustrates this architecture.

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AWS Machine Learning Blog

FEBRUARY 29, 2024

With Knowledge Bases for Amazon Bedrock, you can access detailed information through simple, natural queries. Build a knowledge base for Amazon Bedrock In this section, we demo the process of creating a knowledge base for Amazon Bedrock via the console. For more information, refer to Model access.

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Heartbeat

FEBRUARY 28, 2024

Comet allows data scientists to track their machine learning experiments at every stage, from training to production, while Gradio simplifies the creation of interactive model demos and GUIs with just a few lines of Python code. Gradio is an open-source Python library that simplifies the creation of interactive ML interfaces.

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AWS Machine Learning Blog

AUGUST 1, 2023

With these techniques, marketing, advertisement, and other creative agencies can use generative AI tools to augment their ad creatives process. To dive deeper into the solution and code shown in this demo, check out the GitHub repo. The following is a snippet from inference.py

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AWS Machine Learning Blog

OCTOBER 21, 2024

The model excels at tasks ranging from natural language processing to coding, making it an invaluable resource for researchers, developers, and businesses. model, but the same process can be followed for the Mistral-7B-instruct-v0.3 sets a new standard for user-friendly and powerful AI tools.

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AWS Machine Learning Blog

FEBRUARY 20, 2023

In this post, we provide an overview of how to fine-tune the Stable Diffusion model in two ways: programmatically through JumpStart APIs available in the SageMaker Python SDK , and JumpStart’s user interface (UI) in Amazon SageMaker Studio. Furthermore, we run inference on the deployed endpoint, all using the SageMaker Python SDK.

Algorithm 101

Algorithm Python Machine Learning Machine Learning 101

AWS Machine Learning Blog

NOVEMBER 1, 2023

Through multi-round dialogues, we highlight the capabilities of instruction-oriented zero-shot and few-shot vision language processing, emphasizing its versatility and aiming to capture the interest of the broader multimodal community. The demo implementation code is available in the following GitHub repo. box_threshold=0.5,

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