Data Science Dojo

JUNE 14, 2023

Learn how the synergy of AI and ML algorithms in paraphrasing tools is redefining communication through intelligent algorithms that enhance language expression. Paraphrasing tools in AI and ML algorithms Machine learning is a subset of AI. Pegasus Transformer This is a part of the Transformers library available in Python 3.

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Data Science Dojo

JUNE 14, 2023

Learn how the synergy of AI and ML algorithms in paraphrasing tools is redefining communication through intelligent algorithms that enhance language expression. Paraphrasing tools in AI and ML algorithms Machine learning is a subset of AI. Pegasus Transformer This is a part of the Transformers library available in Python 3.

Machine Learning 195

Machine Learning Machine Learning Algorithm AI 195

AWS Machine Learning Blog

SEPTEMBER 23, 2024

Machine learning (ML) projects are inherently complex, involving multiple intricate steps—from data collection and preprocessing to model building, deployment, and maintenance. To start our ML project predicting the probability of readmission for diabetes patients, you need to download the Diabetes 130-US hospitals dataset.

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AWS Machine Learning Blog

JUNE 6, 2023

PyTorch is a machine learning (ML) framework that is widely used by AWS customers for a variety of applications, such as computer vision, natural language processing, content creation, and more. Our next generation release that is faster, more Pythonic and Dynamic as ever for details. With the recent PyTorch 2.0 Refer to PyTorch 2.0:

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Mlearning.ai

MAY 31, 2023

In this article, we will explore the process of creating a simple chatbot using Python and NLP techniques. Setting up the Development Environment To get started, we need to set up our Python development environment with the necessary libraries and tools. These techniques form the foundation for building intelligent chatbots.

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AWS Machine Learning Blog

AUGUST 22, 2024

In this post, we show you how to convert Python code that fine-tunes a generative AI model in Amazon Bedrock from local files to a reusable workflow using Amazon SageMaker Pipelines decorators. You can use Amazon SageMaker Model Building Pipelines to collaborate between multiple AI/ML teams. Create and run the SageMaker pipeline.

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AWS Machine Learning Blog

FEBRUARY 11, 2025

GraphStorm is a low-code enterprise graph machine learning (ML) framework that provides ML practitioners a simple way of building, training, and deploying graph ML solutions on industry-scale graph data. To download and preprocess the data as an Amazon SageMaker Processing step, use the following code. million edges.

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Towards AI

JUNE 27, 2023

Let’s get started with the best machine learning (ML) developer tools: TensorFlow TensorFlow, developed by the Google Brain team, is one of the most utilized machine learning tools in the industry. PyTorch PyTorch, a Python-based machine learning library, stands out among its peers in the machine learning tools ecosystem.

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AWS Machine Learning Blog

OCTOBER 19, 2023

For many industries, data that is useful for machine learning (ML) may contain personally identifiable information (PII). This post demonstrates how to use Amazon SageMaker Data Wrangler and Amazon Comprehend to automatically redact PII from tabular data as part of your machine learning operations (ML Ops) workflow.

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Machine Learning Machine Learning ML ML 117

Applied Data Science

AUGUST 2, 2021

Download the free, unabridged version here. The most common data science languages are Python and R   —  SQL is also a must have skill for acquiring and manipulating data. Machine Learning In this section, we look beyond ‘standard’ ML practices and explore the 6 ML trends that will set you apart from the pack in 2021.

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Mlearning.ai

AUGUST 11, 2023

ML Implementation — 00 I do not know how I will be proceeding with this project(s) but I plan to document it to some extent. The goal is to utilize ML-Agents with C# and Unity engine to make a couple of ML projects, obviously with visualization. Part 01 of ML Implementation. Until net time. Might take a while to run).

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AWS Machine Learning Blog

APRIL 19, 2023

Right now, most deep learning frameworks are built for Python, but this neglects the large number of Java developers and developers who have existing Java code bases they want to integrate the increasingly powerful capabilities of deep learning into. Business requirements We are the US squad of the Sportradar AI department.

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AWS Machine Learning Blog

SEPTEMBER 29, 2023

In this post, we illustrate how to use a segmentation machine learning (ML) model to identify crop and non-crop regions in an image. Identifying crop regions is a core step towards gaining agricultural insights, and the combination of rich geospatial data and ML can lead to insights that drive decisions and actions.

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Flipboard

FEBRUARY 15, 2023

Amazon SageMaker JumpStart is the machine learning (ML) hub of SageMaker that offers over 350 built-in algorithms, pre-trained models, and pre-built solution templates to help you get started with ML fast. We then use a pre-built MLOps template to bootstrap the ML workflow and provision a CI/CD pipeline with sample code.

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AWS Machine Learning Blog

OCTOBER 2, 2023

You can try out this model with SageMaker JumpStart, a machine learning (ML) hub that provides access to algorithms, models, and ML solutions so you can quickly get started with ML. What is SageMaker JumpStart With SageMaker JumpStart, ML practitioners can choose from a growing list of best-performing foundation models.

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Python ML ML Machine Learning 131

Flipboard

DECEMBER 11, 2024

Second, because data, code, and other development artifacts like machine learning (ML) models are stored within different services, it can be cumbersome for users to understand how they interact with each other and make changes. For Project profile , choose Data analytics and AI-ML model development. Choose Continue.

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Mlearning.ai

JULY 4, 2023

In this article I will show you how to run a version of the Vicuna model in WSL2 with GPU acceleration and prompt the model from Python via an API. The CUDA toolkit can be downloaded from the NVidia website. venv Using python venv is a personal preference — I like how lightweight it is. Simply run python download-model.py

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AWS Machine Learning Blog

MAY 30, 2023

Since its introduction, we’ve helped hundreds of customers optimize their workloads, set guardrails, and improve the visibility of their machine learning (ML) workloads’ cost and usage. When an On-Demand job is launched, it goes through five phases: Starting, Downloading, Training, Uploading, and Completed.

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Flipboard

SEPTEMBER 4, 2023

Envision yourself as an ML Engineer at one of the world’s largest companies. You make a Machine Learning (ML) pipeline that does everything, from gathering and preparing data to making predictions. This is suitable for making a variety of Python applications with other dependencies being added to it at the user’s convenience.

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AWS Machine Learning Blog

APRIL 25, 2024

Hugging Face is a popular open source hub for machine learning (ML) models. AWS and Hugging Face have a partnership that allows a seamless integration through SageMaker with a set of AWS Deep Learning Containers (DLCs) for training and inference in PyTorch or TensorFlow, and Hugging Face estimators and predictors for the SageMaker Python SDK.

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AWS Machine Learning Blog

FEBRUARY 20, 2024

In this post, we discuss deploying scalable machine learning (ML) models for diarizing media content using Amazon SageMaker , with a focus on the WhisperX model. Download the model and its components WhisperX is a system that includes multiple models for transcription, forced alignment, and diarization.

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AWS Machine Learning Blog

FEBRUARY 16, 2024

You can try out this model with SageMaker JumpStart, a machine learning (ML) hub that provides access to algorithms, models, and ML solutions so you can quickly get started with ML. You can also download the license agreement. Code Llama Code Llama is a model released by Meta that is built on top of Llama 2.

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phData

MARCH 22, 2023

As companies continue to adopt machine learning (ML) in their workflows, the demand for scalable and efficient tools has increased. In this blog post, we will explore the performance benefits of Snowpark for ML workloads and how it can help businesses make better use of their data. Total': (t_write - t_start).total_seconds()

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AWS Machine Learning Blog

NOVEMBER 29, 2023

Amazon SageMaker Studio provides a fully managed solution for data scientists to interactively build, train, and deploy machine learning (ML) models. With this launch, you can programmatically run notebooks as jobs using APIs provided by Amazon SageMaker Pipelines , the ML workflow orchestration feature of Amazon SageMaker.

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AWS Machine Learning Blog

MAY 1, 2024

Using the Neuron Distributed library with SageMaker SageMaker is a fully managed service that provides developers, data scientists, and practitioners the ability to build, train, and deploy machine learning (ML) models at scale. Health checks are currently enabled for the TRN1 instance family as well as P* and G* GPU-based instance types.

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PyImageSearch

DECEMBER 4, 2023

Home Table of Contents ML Days in Tashkent — Day 1: City Tour Arriving at Tashkent! This blog is the 1st of a 3-part series: ML Days in Tashkent — Day 1: City Tour (this tutorial) ML Days in Tashkent — Day 2: Sprints and Sessions ML Days in Tashkent — Day 3: Demos and Workshops ML Days in Tashkent — Day 1: City Tour Arriving at Tashkent!

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AWS Machine Learning Blog

OCTOBER 16, 2023

As an AI-powered solution, Veriff needs to create and run dozens of machine learning (ML) models in a cost-effective way. This approach was initially used for all company services, including microservices that run expensive computer vision ML models. Some of these models required deployment on GPU instances.

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AWS Machine Learning Blog

JUNE 4, 2024

Solution overview We use Terraform to download a public dataset from the Hugging Face Hub , convert it to JSONL format, and upload it to an Amazon Simple Storage Service (Amazon S3) bucket with a versioned prefix. Configure your local Python virtual environment. Download the DialogSum public dataset and convert it to JSONL.

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Flipboard

JULY 24, 2023

’ If someone wants to use Quivr without any limitations, then they can download it locally on their device. You should also have the official, and the latest version of Python preinstalled on your device. It has an official website from which you can access the premium version of Quivr by clicking on the button ‘Try demo.’

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AWS Machine Learning Blog

MAY 25, 2023

Dockerfile requirements.txt Create an Amazon Elastic Container Registry (Amazon ECR) repository in us-east-1 and push the container image created by the downloaded Dockerfile. Abhijit Kalita is a Senior AI/ML Evangelist at Amazon Web Services. Clone the GitHub repo to create the container image: app.py amazonaws.com docker build -t.

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AWS Machine Learning Blog

MAY 15, 2024

ONNX is an open source machine learning (ML) framework that provides interoperability across a wide range of frameworks, operating systems, and hardware platforms. AWS Graviton3 processors are optimized for ML workloads, including support for bfloat16, Scalable Vector Extension (SVE), and Matrix Multiplication (MMLA) instructions.

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Mlearning.ai

APRIL 6, 2023

Automate and streamline our ML inference pipeline with SageMaker and Airflow Building an inference data pipeline on large datasets is a challenge many companies face. SageMaker Batch Job Allows you to run batch inference on large datasets and generate predictions in a batch mode using machine learning (ML) models hosted in SageMaker.

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AWS Machine Learning Blog

MAY 2, 2024

You are responsible for reviewing and complying with applicable license terms and making sure they are acceptable for your use case before downloading or using the content. You can access the Meta Llama 3 FMs through SageMaker JumpStart on the Amazon SageMaker Studio console and the SageMaker Python SDK.

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AWS Machine Learning Blog

JULY 24, 2024

Fine-tuning an LLM can be a complex workflow for data scientists and machine learning (ML) engineers to operationalize. Solution overview Running hundreds of experiments, comparing the results, and keeping a track of the ML lifecycle can become very complex. In this example, we download the data from a Hugging Face dataset.

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AWS Machine Learning Blog

OCTOBER 10, 2023

Machine learning (ML), especially deep learning, requires a large amount of data for improving model performance. It is challenging to centralize such data for ML due to privacy requirements, high cost of data transfer, or operational complexity. The ML framework used at FL clients is TensorFlow.

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The MLOps Blog

JANUARY 26, 2024

Luckily, we have tried and trusted tools and architectural patterns that provide a blueprint for reliable ML systems. In this article, I’ll introduce you to a unified architecture for ML systems built around the idea of FTI pipelines and a feature store as the central component. But what is an ML pipeline?

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Pickl AI

NOVEMBER 4, 2024

Summary: Python for Data Science is crucial for efficiently analysing large datasets. With numerous resources available, mastering Python opens up exciting career opportunities. Introduction Python for Data Science has emerged as a pivotal tool in the data-driven world. As the global Python market is projected to reach USD 100.6

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