ODSC - Open Data Science

OCTOBER 11, 2023

New algorithms/software can help you systematically curate your data via automation. These techniques are based on years of research from my team, investigating what sorts of data problems can be detected algorithmically using information from a trained model.

Auto-classification 52

Auto-classification Auto-complete Data Drift Machine Learning 52

Dlabs.ai

JUNE 11, 2019

To train a computer algorithm when you don’t have any data. These days, with a little ingenuity, you can automate the task. In deep learning, a computer algorithm uses images, text, or sound to learn to perform a set of classification tasks. Say, you want to auto-detect headers in a document. It’s a tricky task.

Deep Learning 52

Deep Learning Algorithm Convolutional Neural Networks Neural Network 52

Snorkel AI

OCTOBER 31, 2023

Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification Guha et al. Additionally, the researchers share a simple counterfactual fairness correction algorithm. A case for reframing automated medical image classification as segmentation Hooper et al.

AI Research 59

AI Research AI Researcher Auto-classification Large Language Models 59

Unite.AI

JUNE 24, 2024

By establishing standardized workflows, automating repetitive tasks, and implementing robust monitoring and governance mechanisms, MLOps enables organizations to accelerate model development, improve deployment reliability, and maximize the value derived from ML initiatives.

Data Drift 124

Data Drift Machine Learning Data Scientist DevOps 124

Snorkel AI

OCTOBER 31, 2023

Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification Guha et al. Additionally, the researchers share a simple counterfactual fairness correction algorithm. A case for reframing automated medical image classification as segmentation Hooper et al.

AI Research 52

AI Research AI Researcher Auto-classification Large Language Models 52

AWS Machine Learning Blog

MAY 3, 2023

Feature engineering refers to the process where relevant variables are identified, selected, and manipulated to transform the raw data into more useful and usable forms for use with the ML algorithm used to train a model and perform inference against it. The final outcome is an auto scaling, robust, and dynamically monitored solution.

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Auto-classification Auto-complete Machine Learning Metadata 87

Pickl AI

JANUARY 23, 2023

People don’t even need the in-depth knowledge of the various machine learning algorithms as it contains pre-built libraries. This framework can perform classification, regression, etc., Most of the organizations make use of Caffe in order to deal with computer vision and classification related problems.

Machine Learning 52

Machine Learning ML Neural Network Auto-classification 52

The MLOps Blog

JUNE 27, 2023

For example, if your team works on recommender systems or natural language processing applications, you may want an MLOps tool that has built-in algorithms or templates for these use cases. This includes features for hyperparameter tuning, automated model selection, and visualization of model metrics.

Metadata 134

Metadata Machine Learning Data Scientist Data Quality 134

AWS Machine Learning Blog

OCTOBER 6, 2023

For instance, in ecommerce, image-to-text can automate product categorization based on images, enhancing search efficiency and accuracy. CLIP model CLIP is a multi-modal vision and language model, which can be used for image-text similarity and for zero-shot image classification.

Generative AI 121

Generative AI Prompt Engineer Prompt Engineering Computer Vision 121

AWS Machine Learning Blog

NOVEMBER 22, 2023

Codify Operations for Efficiency and Reproducibility By performing operations as code and incorporating automated deployment methodologies, organizations can achieve scalable, repeatable, and consistent processes. Build and release optimization – This area emphasizes the implementation of standardized DevSecOps processes.

IDP 108

IDP Data Extraction Auto-classification Machine Learning 108

Defined.ai blog

SEPTEMBER 21, 2023

Natural Language Processing seeks to automate the interpretation of human language by machines. However, NLP has reentered with the development of more sophisticated algorithms, deep learning, and vast datasets in recent years. Imagine training a computer to navigate this intricately woven tapestry—it’s no small feat!

Natural Language Processing 52

Natural Language Processing NLP Auto-classification Data Mining 52

Snorkel AI

JANUARY 12, 2023

Language complexity: Some languages, such as Chinese and Arabic, have complex characters and scripts that can make them more difficult to process using NLP algorithms. For text classification, however, there are many similarities. Snorkel Flow’s “Auto-Suggest Key Terms” feature works on any language with “white-space” tokenization.

BERT 52

BERT NLP Auto-classification Natural Language Processing 52

Unite.AI

DECEMBER 19, 2023

During the training phase, we add “noise,” which changes the raw data from the files we feed into our algorithm, in order to automatically generate slight “mutations,” which are fed in each training cycle during our training phase. From there, we validate and classify data ourselves with algorithms we developed internally.

Neural Network 147

Neural Network Deep Learning Metadata Auto-classification 147

AWS Machine Learning Blog

JUNE 23, 2023

Amazon SageMaker Data Wrangler is a single visual interface that reduces the time required to prepare data and perform feature engineering from weeks to minutes with the ability to select and clean data, create features, and automate data preparation in machine learning (ML) workflows without writing any code. Choose Add step.

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Auto-complete Auto-classification ML Data Quality 86

AWS Machine Learning Blog

JUNE 3, 2024

For Problem type , select Classification. In the following example, we drop the columns Timestamp, Country, state, and comments, because these features will have least impact for classification of our model. For Training method , select Auto. For more information, see Training modes and algorithm support. Choose Create.

Generative AI 114

Generative AI Categorization Auto-complete Auto-classification 114

AWS Machine Learning Blog

JULY 31, 2023

In this post, we show how a business analyst can evaluate and understand a classification churn model created with SageMaker Canvas using the Advanced metrics tab. Cost-sensitive classification – In some applications, the cost of misclassification for different classes can be different.

Auto-classification 90

Auto-classification Machine Learning Auto-complete ML 90

AWS Machine Learning Blog

OCTOBER 8, 2024

SageMaker AutoMLV2 is part of the SageMaker Autopilot suite, which automates the end-to-end machine learning workflow from data preparation to model deployment. It provides a straightforward way to create high-quality models tailored to your specific problem type, be it classification, regression, or forecasting, among others.

Machine Learning 93

Machine Learning Auto-complete Auto-classification Metadata 93

Pickl AI

MARCH 10, 2023

Furthermore, it ensures that data is consistent while effectively increasing the readability of the data’s algorithm. One way to solve Data Science’s challenges in Data Cleaning and pre-processing is to enable Artificial Intelligence technologies like Augmented Analytics and Auto-feature Engineering.

Data Scientist 52

Data Scientist Data Science Data Integration Auto-classification 52

The Stanford AI Lab Blog

MARCH 28, 2022

[Summary] tl;dr: A tremendous amount of effort has been poured into training AI algorithms to competitively play games that computers have traditionally had trouble with, such as the retro games published by Atari, Go, DotA, and StarCraft II. Can the same algorithms that master Atari games help us grade these game assignments?

Algorithm 52

Algorithm Auto-classification Automation Auto-complete 52

AWS Machine Learning Blog

APRIL 20, 2023

Amazon SageMaker Inference Recommender is a capability of Amazon SageMaker that reduces the time required to get ML models in production by automating load testing and model tuning across SageMaker ML instances. We train an XGBoost model for a classification task on a credit card fraud dataset. large", "ml.m5.xlarge",

ML 93

ML Auto-classification Python Auto-complete 93

AWS Machine Learning Blog

NOVEMBER 14, 2024

Optionally, if Account A and Account B are part of the same AWS Organizations, and the resource sharing is enabled within AWS Organizations, then the resource sharing invitation are auto accepted without any manual intervention. It’s a binary classification problem where the goal is to predict whether a customer is a credit risk.

ML 89

ML Auto-complete Machine Learning Auto-classification 89

The MLOps Blog

MARCH 12, 2024

Monitoring Monitor model performance for data drift and model degradation, often using automated monitoring tools. Feedback loops: Use automated and human feedback to improve prompt design continuously. Models are part of chains and agents, supported by specialized tools like vector databases.

Prompt Engineer 52

Prompt Engineer Prompt Engineering Large Language Models LLM 52

AWS Machine Learning Blog

MARCH 2, 2023

Transformer-based language models such as BERT ( Bidirectional Transformers for Language Understanding ) have the ability to capture words or sentences within a bigger context of data, and allow for the classification of the news sentiment given the current state of the world. W&B Sweeps will automate this kind of exploration.

BERT 86

BERT Deep Learning Metadata Auto-complete 86

Snorkel AI

FEBRUARY 27, 2023

Take that canonical spam classification example: if you see the phrase wire transfer , maybe it’s more likely to be spam. Rather than just throwing it away, we can use it to auto-generate labels and train machine-learning models that can then learn to extend beyond what’s in these expansive but sometimes brittle knowledge bases.

Machine Learning 52

Machine Learning AI AI Large Language Models 52

Snorkel AI

FEBRUARY 27, 2023

Take that canonical spam classification example: if you see the phrase wire transfer , maybe it’s more likely to be spam. Rather than just throwing it away, we can use it to auto-generate labels and train machine-learning models that can then learn to extend beyond what’s in these expansive but sometimes brittle knowledge bases.

Machine Learning 52

Machine Learning AI AI Large Language Models 52

AWS Machine Learning Blog

SEPTEMBER 6, 2023

You can easily try out these models and use them with SageMaker JumpStart, which is a machine learning (ML) hub that provides access to algorithms, models, and ML solutions so you can quickly get started with ML. What is Llama 2 Llama 2 is an auto-regressive language model that uses an optimized transformer architecture. Default is 5.

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The MLOps Blog

JUNE 6, 2023

Efficiency: Pipelines automate repetitive tasks, reducing manual intervention and saving time. Experimentation: With a structured pipeline, it’s easier to track experiments and compare different models or algorithms. Model Training: The preprocessed data is fed into the chosen ML algorithm to train the model. Build the pipeline.

ML 52

ML Machine Learning Auto-classification Auto-complete 52

AWS Machine Learning Blog

JULY 16, 2024

These models often require enormous computational resources and sophisticated infrastructure to handle the vast amounts of data and complex algorithms involved. This operator simplifies the process of running distributed training jobs by automating the deployment and scaling of the necessary components.

Generative AI 127

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AWS Machine Learning Blog

JANUARY 9, 2023

The base models can be diverse and trained by different algorithms. For example, an image classification use case may use three different models to perform the task. The scatter-gather pattern allows you to combine results from inferences run on three different models and pick the most probable classification model.

ML 85

ML Auto-complete Auto-classification Deep Learning 85

AWS Machine Learning Blog

JANUARY 26, 2023

SageMaker provides automated model tuning , which manages the undifferentiated heavy lifting of provisioning and managing compute infrastructure to run several iterations and select the optimized model candidate from training. Best Egg trains multiple credit models using classification and regression algorithms.

ML 87

ML Auto-complete Data Scientist Auto-classification 87

AWS Machine Learning Blog

JANUARY 17, 2024

Llama 2 is an auto-regressive generative text language model that uses an optimized transformer architecture. As a publicly available model, Llama 2 is designed for many NLP tasks such as text classification, sentiment analysis, language translation, language modeling, text generation, and dialogue systems.

Auto-complete 126

Auto-complete Python Deep Learning Machine Learning 126

Topbots

JUNE 29, 2023

After parsing a question, an algorithm encodes it into a structured logical form in the query language of choice, such as SQL. High-quality , so that the Text2SQL algorithm does not have to deal with excessive noise (inconsistencies, empty values etc.) in the data. section “Enriching the prompt with database information”).

Auto-complete 52

Auto-complete Algorithm Data Scientist Auto-classification 52

AWS Machine Learning Blog

JANUARY 31, 2024

In the first part of this three-part series, we presented a solution that demonstrates how you can automate detecting document tampering and fraud at scale using AWS AI and machine learning (ML) services for a mortgage underwriting use case. Specifically, the JPEG algorithm operates on an 8×8 pixel grid.

Computer Vision 115

Computer Vision Auto-complete Deep Learning Auto-classification 115