Smart Data Collective

FEBRUARY 3, 2022

The Right Use of Tools To Deal With Data. Business teams significantly rely upon data for self-service tools and more. Businesses will need to opt for data preparation and analytics tasks, ranging from finance to marketing. Therefore, businesses use tools that will ease the process to get the right data.

Analytics 145

Analytics Analytics Machine Learning Machine Learning 145

IBM Journey to AI blog

AUGUST 12, 2024

Primary activities AIOps relies on big data-driven analytics , ML algorithms and other AI-driven techniques to continuously track and analyze ITOps data. The process includes activities such as anomaly detection, event correlation, predictive analytics, automated root cause analysis and natural language processing (NLP).

Big Data 106

Big Data Big Data ML ML 106

The MLOps Blog

JUNE 27, 2023

Learn more The Best Tools, Libraries, Frameworks and Methodologies that ML Teams Actually Use – Things We Learned from 41 ML Startups [ROUNDUP] Key use cases and/or user journeys Identify the main business problems and the data scientist’s needs that you want to solve with ML, and choose a tool that can handle them effectively.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

IBM Journey to AI blog

JULY 17, 2023

This allows users to accomplish different Natural Language Processing (NLP) functional tasks and take advantage of IBM vetted pre-trained open-source foundation models. Encoder-decoder and decoder-only large language models are available in the Prompt Lab today. To bridge the tuning gap, watsonx.ai

AI 74

AI AI Machine Learning Machine Learning 74

IBM Journey to AI blog

AUGUST 11, 2023

Because the machine learning lifecycle has many complex components that reach across multiple teams, it requires close-knit collaboration to ensure that hand-offs occur efficiently, from data preparation and model training to model deployment and monitoring. How to use ML to automate the refining process into a cyclical ML process.

Data Science 68

Data Science Machine Learning Machine Learning ML 68

Pickl AI

SEPTEMBER 5, 2024

Data Preparation: Cleaning, transforming, and preparing data for analysis and modelling. Algorithm Development: Crafting algorithms to solve complex business problems and optimise processes.

Azure 52

Azure Data Scientist Data Science Machine Learning 52

AWS Machine Learning Blog

SEPTEMBER 11, 2024

The benchmark used is the RoBERTa-Base, a popular model used in natural language processing (NLP) applications, that uses the transformer architecture. Historical data is normally (but not always) independent inter-day, meaning that days can be parsed independently.

AWS 120

AWS ML ML Clustering 120