ODSC - Open Data Science

FEBRUARY 28, 2023

Going from Data to Insights LexisNexis At HPCC Systems® from LexisNexis® Risk Solutions you’ll find “a consistent data-centric programming language, two processing platforms, and a single, complete end-to-end architecture for efficient processing.” These tools are designed to help companies derive insights from big data.

Data Science 96

Data Science Auto-complete Machine Learning AI 96

Towards AI

SEPTEMBER 27, 2023

In previous articles, we explored how SageMaker can accelerate the processes of data understanding, transformation, and feature creation in model development. Data quality and coverage play a key role in the outcomes of the model. Avoid overfitting: The model should understand patterns, not just memorize them.

Data Scientist 64

Data Scientist Auto-complete Automation Algorithm 64

AWS Machine Learning Blog

JULY 31, 2023

A perfect F1 score of 1 indicates that the model has achieved both perfect precision and perfect recall, and a score of 0 indicates that the model’s predictions are completely wrong. Finally, when it’s complete, the pane will show a list of columns with its impact on the model.

Auto-classification 98

Auto-classification Machine Learning ML Auto-complete 98

The MLOps Blog

JANUARY 23, 2025

Source Architecture and training PaLM-E is a decoder-only LLM that auto-regressively generates text using a multimodal prompt consisting of text, tokenized image embeddings, and state estimates representing quantities like a robot’s position, orientation, and velocity. In a survey paper, Paul Liang et al.

Large Language Models 59

Large Language Models Auto-classification LLM Robotics 59

Snorkel AI

FEBRUARY 8, 2023

Data science and machine learning teams use Snorkel Flow’s programmatic labeling to intelligently capture knowledge from various sources—such as previously labeled data (even when imperfect), heuristics from subject matter experts, business logic, and even the latest foundation models —and then scale this knowledge to label large quantities of data.

Auto-complete 52

Auto-complete Data Quality Machine Learning Data Science 52

Snorkel AI

FEBRUARY 8, 2023

Data science and machine learning teams use Snorkel Flow’s programmatic labeling to intelligently capture knowledge from various sources—such as previously labeled data (even when imperfect), heuristics from subject matter experts, business logic, and even the latest foundation models —and then scale this knowledge to label large quantities of data.

Auto-complete 52

Auto-complete Data Quality Machine Learning Data Science 52

Pickl AI

APRIL 9, 2023

This report exhibits a complete data presentation, making it easier to understand the information stored behind it. It works on cognitive technology, which uses rephrasing, auto-fill and suggestions to fulfil the user’s search requirements. The post Power BI Tutorial– A Complete Guide appeared first on Pickl AI.

Auto-complete 52

Auto-complete Business Intelligence Data Quality AI 52

The MLOps Blog

SEPTEMBER 26, 2024

Causes of hallucinations include insufficient training data, misalignment, attention limitations, and tokenizer issues. Effective mitigation strategies involve enhancing data quality, alignment, information retrieval methods, and prompt engineering. In extreme cases, certain tokens can completely break an LLM.

LLM 72

LLM Prompt Engineering Prompt Engineer Auto-complete 72

Chatbots Life

MAY 19, 2023

Your staff can auto-resolve issues using this ticketing system. They achieve this by asking the user for input, seeking confirmation, and collecting essential data for back-end business systems, boosting data quality and avoiding mistakes. Modern service desks offer an automated ticketing system for staff.

Chatbots 69

Chatbots Automation Auto-complete NLP 69

Viso.ai

DECEMBER 18, 2023

1: Variational Auto-Encoder. A Variational Auto-Encoder (VAE) generates synthetic data via double transformation, known as an encoded-decoded architecture. First, it encodes the real data into a latent space (a lower-dimensional representation). Then, it decodes this data back into simulated data.

Computer Vision 52

Computer Vision Neural Network Auto-complete Data Scarcity 52

AWS Machine Learning Blog

APRIL 17, 2023

SageMaker LMI containers includes model download optimization by using the s5cmd library to speed up the model download time and container startup times, and eventually speed up auto scaling on SageMaker. A complete example that illustrates the no-code option can be found in the following notebook.

Prompt Engineering 103

Prompt Engineering Prompt Engineer Deep Learning Machine Learning 103

The MLOps Blog

JULY 18, 2023

We strive to do that, but sometimes you run into a corner where you have no choice but to really get quality results you have to do that. But it’s absolutely critical for most people in our space that you do some type of auto-scaling. How do you ensure data quality when building NLP products? Data quality is critical.

Conversational AI 52

Conversational AI Natural Language Processing Machine Learning AI 52

AWS Machine Learning Blog

NOVEMBER 14, 2024

It includes processes for monitoring model performance, managing risks, ensuring data quality, and maintaining transparency and accountability throughout the model’s lifecycle. Following are the steps completed by using APIs to create and share a model package group across accounts. In Account A, create a model package group.

ML 104

ML Machine Learning Auto-complete Auto-classification 104

Unite.AI

SEPTEMBER 4, 2023

Technical Deep Dive of Llama 2 For training the Llama 2 model; like its predecessors, it uses an auto-regressive transformer architecture , pre-trained on an extensive corpus of self-supervised data. Data quality and diversity are just as pivotal as volume in these scenarios.

ChatGPT 290

ChatGPT Auto-complete Large Language Models LLM 290

AWS Machine Learning Blog

AUGUST 15, 2024

Starting today, you can prepare your petabyte-scale data and explore many ML models with AutoML by chat and with a few clicks. In this post, we show you how you can complete all these steps with the new integration in SageMaker Canvas with Amazon EMR Serverless without writing code.

ML 125

ML Generative AI Auto-complete Data Quality 125

Unite.AI

JANUARY 22, 2025

Self-service and collaboration: With Nexla, data consumers not only access data on their own and build Nexsets and flows. They can collaborate and share their work via a marketplace that ensures data is in the right format and improves productivity through reuse. Auto generation: Integration and GenAI are both hard.

Auto-complete 147

Auto-complete Automation Machine Learning Data Integration 147