Mlearning.ai

FEBRUARY 4, 2023

TL;DR Structuring Python projects is very important for proper internal working, as well as for distribution to other users in the form of packages. There are two main general structures: the flat layout vs the src layout as clearly explained in the official Python packaging guide here. Package your project source code folder.

Python 52

Python Metadata Explainability Data Science 52

AWS Machine Learning Blog

MARCH 29, 2023

In this post, we discuss how the IEO developed UNDP’s artificial intelligence and machine learning (ML) platform—named Artificial Intelligence for Development Analytics (AIDA)— in collaboration with AWS, UNDP’s Information and Technology Management Team (UNDP ITM), and the United Nations International Computing Centre (UNICC).

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ML Metadata Data Ingestion Data Extraction 69

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. When selecting the Docker image, consider the following settings: framework (Hugging Face), task (inference), Python version, and hardware (for example, GPU).

Metadata 95

Metadata Auto-complete Machine Learning Deep Learning 95

AWS Machine Learning Blog

AUGUST 16, 2023

Training machine learning (ML) models to interpret this data, however, is bottlenecked by costly and time-consuming human annotation efforts. Additionally, each folder contains a JSON file with the image metadata. We store the BigEarthNet-S2 images and metadata file in an S3 bucket. tif" --include "_B03.tif"

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Metadata Data Scientist Generative AI Natural Language Processing 71

AWS Machine Learning Blog

NOVEMBER 27, 2023

There could also be a lot of low-quality contents or bot-generated texts, which can be filtered out using accompanying metadata (e.g., Consider the following machine learning (ML) problem: user asks a large language model (LLM) question: “How to filter and search models in Amazon Bedrock?”. Choose Python (PySpark) for this use-case.

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Generative AI Metadata LLM Python 74

The MLOps Blog

JANUARY 23, 2023

Dolt LakeFS Delta Lake Pachyderm Git-like versioning Database tool Data lake Data pipelines Experiment tracking Integration with cloud platforms Integrations with ML tools Examples of data version control tools in ML DVC Data Version Control DVC is a version control system for data and machine learning teams. DVC Git LFS neptune.ai

ML 52

ML Machine Learning Metadata Data Scientist 52

AWS Machine Learning Blog

APRIL 5, 2023

Amazon SageMaker Serverless Inference is a purpose-built inference service that makes it easy to deploy and scale machine learning (ML) models. Data overview and preparation You can use a SageMaker Studio notebook with a Python 3 (Data Science) kernel to run the sample code. We use the first metadata file in this demo.

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Metadata ML Neural Network Python 87

Marktechpost

AUGUST 8, 2023

In the ever-evolving landscape of machine learning, feature management has emerged as a key pain point for ML Engineers at Airbnb. Chronon empowers ML practitioners to define features and centralize data computation for model training and production inference, guaranteeing accuracy and consistency throughout the process.

Machine Learning 98

Machine Learning ML Engineer Data Ingestion ML 98

Heartbeat

JANUARY 19, 2024

In this article you will learn how to log the YOLOPandas prompts with comet-llm, keep track of the number of tokens used in USD($), and log your metadata. link] Through the log_prompt function, the prompt, its associated response, and metadata like token usage, total tokens model, etc. Check out the Comet LLMOps tool.

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LLM Metadata Prompt Engineer Prompt Engineering 52

Heartbeat

MARCH 28, 2023

A complete guide to building a deep learning project with PyTorch, tracking an Experiment with Comet ML, and deploying an app with Gradio on HuggingFace Image by Freepik AI tools such as ChatGPT, DALL-E, and Midjourney are increasingly becoming a part of our daily lives. This is when Comet ML comes into play. Installing comet_ml # !pip

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Deep Learning ML Convolutional Neural Networks Machine Learning 52

Marktechpost

AUGUST 13, 2023

Most publicly available image databases are difficult to edit beyond crude image augmentations and lack fine-grained metadata. Also, don’t forget to join our 28k+ ML SubReddit , 40k+ Facebook Community, Discord Channel , and Email Newsletter , where we share the latest AI research news, cool AI projects, and more.

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AI Researcher AI Research Neural Network Metadata 95

AWS Machine Learning Blog

MAY 5, 2023

In this post, we discuss a machine learning (ML) solution for complex image searches using Amazon Kendra and Amazon Rekognition. Amazon Kendra is an intelligent search service powered by ML, and Amazon Rekognition is an ML service that can identify objects, people, text, scenes, and activities from images or videos.

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Metadata ETL ML Data Ingestion 101

AWS Machine Learning Blog

APRIL 3, 2024

Amazon SageMaker Studio – It is an integrated development environment (IDE) for machine learning (ML). ML practitioners can perform all ML development steps—from preparing your data to building, training, and deploying ML models. Rupinder Grewal is a Senior AI/ML Specialist Solutions Architect with AWS.

Machine Learning 100

Machine Learning Generative AI Metadata ML 100

AWS Machine Learning Blog

FEBRUARY 14, 2023

Amazon Kendra is an intelligent search service powered by machine learning (ML). Solution overview To solve this problem, you can identify one or more unique metadata information that is associated with the documents being indexed and searched. In Amazon Kendra, you provide document metadata attributes using custom attributes.

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Chatbots AI Chatbots Metadata IDP 79

AWS Machine Learning Blog

NOVEMBER 8, 2023

The MONAI AI models and applications can be hosted on Amazon SageMaker , which is a fully managed service to deploy machine learning (ML) models at scale. AHI provides API access to ImageSet metadata and ImageFrames. Metadata contains all DICOM attributes in a JSON document.

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Metadata AI AI Python 95

TheSequence

JULY 12, 2023

In 2018, I joined Cruise and cofounded the ML Infrastructure team there. We built many critical platform systems that enabled the ML teams to develop and ship models much faster, which contributed to the commercial launch of robotaxis in San Francisco in 2022. This required large end-to-end pipelines.

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ML Python Machine Learning Metadata 97

ODSC - Open Data Science

SEPTEMBER 21, 2023

The following is an extract from Andrew McMahon’s book , Machine Learning Engineering with Python, Second Edition. Secondly, to be a successful ML engineer in the real world, you cannot just understand the technology; you must understand the business. What does an ML solution look like?

Machine Learning 98

Machine Learning ML Engineer ML Data Science 98

AWS Machine Learning Blog

DECEMBER 13, 2023

Machine learning (ML) models do not operate in isolation. To deliver value, they must integrate into existing production systems and infrastructure, which necessitates considering the entire ML lifecycle during design and development. GitHub serves as a centralized location to store, version, and manage your ML code base.

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ML Automation Metadata Software Development 100

AWS Machine Learning Blog

APRIL 4, 2023

AWS provides various services catered to time series data that are low code/no code, which both machine learning (ML) and non-ML practitioners can use for building ML solutions. We recommend running this notebook on Amazon SageMaker Studio , a web-based, integrated development environment (IDE) for ML.

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Python Explainability Data Ingestion Machine Learning 81

AWS Machine Learning Blog

DECEMBER 19, 2023

Artificial intelligence (AI) and machine learning (ML) are becoming an integral part of systems and processes, enabling decisions in real time, thereby driving top and bottom-line improvements across organizations. However, putting an ML model into production at scale is challenging and requires a set of best practices.

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Machine Learning ML Engineer DevOps ML 104

AWS Machine Learning Blog

JULY 24, 2023

At the same time, Patsnap is embracing the power of machine learning (ML) to develop features that can continuously improve user experiences on the platform. Install the required Python packages. The following Python packages are needed for this two-step conversion: tabulate toml torch sentencepiece==0.1.95 model_fp16.onnx

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Metadata Generative AI Natural Language Processing Deep Learning 66

AWS Machine Learning Blog

APRIL 21, 2023

The last attribute, Churn , is the attribute that we want the ML model to predict. The repository also includes additional Python source code with helper functions, used in the setup notebook, to set up required permissions. In Studio, you can choose any step to see its key metadata. Setup.ipynb |— 1.SageMakerPipeline-BaselineData-Train.ipynb

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Data Drift Metadata Data Quality ML 74

AWS Machine Learning Blog

JANUARY 17, 2023

Amazon SageMaker Studio is a fully integrated development environment (IDE) for machine learning (ML) partly based on JupyterLab 3. Studio provides a web-based interface to interactively perform ML development tasks required to prepare data and build, train, and deploy ML models. cdk.json – Contains metadata, and feature flags.

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Software Engineer ML Engineer ML Machine Learning 75

The MLOps Blog

MAY 10, 2023

When working on real-world machine learning (ML) use cases, finding the best algorithm/model is not the end of your responsibilities. Reusability & reproducibility: Building ML models is time-consuming by nature. Save vs package vs store ML models Although all these terms look similar, they are not the same.

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Python Metadata ML Deep Learning 106

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. Collaboration : Share experiments with team members, making it a collaborative hub for your ML projects.

Machine Learning 52

Machine Learning Data Scientist LLM ML 52

ODSC - Open Data Science

JUNE 8, 2023

Taipy The inspiration for this open-source software for Python developers was the frustration felt by those who were trying, and struggling, to bring AI algorithms to end-users. To deliver on their commitment to enhancing human ingenuity, SAS’s ML toolkit focuses on automation and more to provide smarter decision-making.

Machine Learning 52

Machine Learning Data Science Metadata AI 52

Heartbeat

SEPTEMBER 22, 2023

Try CometLLM, a free, open-source tool to log, visualize, and search your LLM prompts and metadata. Although we won’t show the full code here, you can envision writing lines of Python code to read the dataset, split it into parts for training and testing, and then use magic Adjust the super parameter to create this super smart crystal ball.

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Machine Learning ML Algorithm Automation 64

TheSequence

OCTOBER 18, 2023

Most recently, she was the founding engineer at Predibase, where she led the ML infrastructure team. In earlier roles, she was part of the cross-functional ML team within Apple's Special Projects Group and developed computer vision models for autonomous driving perception systems at Drive.ai. Great point!

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LLM Large Language Models Chatbots AI 59

Heartbeat

FEBRUARY 21, 2023

Visualize and filter bounding boxes, labels, and metadata without any extra setup. But first, as you may know with other Python libraries, you’ll need to install it in your environment or create a brand new venv. Any data, any environment. Kangas can run in a notebook or as a standalone app, both locally and remotely.

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Computer Vision Deep Learning Metadata Data Scientist 52

AWS Machine Learning Blog

APRIL 7, 2023

As one of the most prominent use cases to date, machine learning (ML) at the edge has allowed enterprises to deploy ML models closer to their end-customers to reduce latency and increase responsiveness of their applications. Even ground and aerial robotics can use ML to unlock safer, more autonomous operations. sourcedir.tar.gz

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BERT Metadata Natural Language Processing ML 80

AWS Machine Learning Blog

MAY 5, 2023

Solution overview Ground Truth is a fully self-served and managed data labeling service that empowers data scientists, machine learning (ML) engineers, and researchers to build high-quality datasets. For our example use case, we work with the Fashion200K dataset , released at ICCV 2017.

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Metadata Computer Vision Machine Learning Data Scientist 75

Heartbeat

MARCH 7, 2023

Image from Author Through the get_schema() , as shown in the above image, we can get information about how is set the data and metadata of our DataGrid and also the data types of each of them. All the Hugging Face open-source projects are available on their GitHub page, and they include Transformers, Datasets and Tokenizers. installed.

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Metadata Deep Learning Computer Vision Machine Learning 52

The MLOps Blog

OCTOBER 3, 2023

This article was originally an episode of the ML Platform Podcast , a show where Piotr Niedźwiedź and Aurimas Griciūnas, together with ML platform professionals, discuss design choices, best practices, example tool stacks, and real-world learnings from some of the best ML platform professionals. How do I develop my body of work?

ML 52

ML Data Scientist Machine Learning Data Science 52

Mlearning.ai

FEBRUARY 11, 2023

A Step-To-Step Guide to the Deployment of Python Flask Apps on Heroku Photo: Pixabay on Pexels Introduction We built our model. We recommend creating and installing a virtual environment to install Flask in Python. It is a folder with a local copy of the Python interpreter with its packages installed.

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Python Machine Learning Metadata Algorithm 52

Heartbeat

SEPTEMBER 28, 2023

In this article, we take a deep dive into a machine learning project aimed at predicting customer churn and explore how Comet ML, a powerful machine learning experiment tracking platform, plays a key role in increasing project success. ?I Try CometLLM, a free, open-source tool to log, visualize, and search your LLM prompts and metadata.

Machine Learning 52

Machine Learning Categorization ML Data Scientist 52

Heartbeat

NOVEMBER 22, 2023

Setting Up the Environment First, we’ll use Github Codespace and Python in conjunction with the OpenAI GPT-3.5 Make sure you have the required Python packages installed and obtain your OpenAI API and Comet API keys. Feel free to check out this GitHub repository as we move forward in the process.

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Chatbots OpenAI Deep Learning Machine Learning 52

Heartbeat

AUGUST 16, 2023

Steps followed 1) Data Collection Creating the Google credentials and generating the YouTube Data API Key Scraping Youtube links using Python code and a generated API Key Downloading the videos of the links saved 2) Setup and Installations Setting up the virtual Python 3.9 google-api-python-client==2.83.0 ml-dtypes==0.0.4

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Python Computer Vision Deep Learning ML 52