Pickl AI

MARCH 4, 2024

Optimising Power BI reports for performance ensures efficient data analysis. Power BI proficiency opens doors to lucrative data analytics and business intelligence opportunities, driving organisational success in today’s data-driven landscape. Loading data into Power BI is a straightforward process.

Power BI 52

Power BI Data Analysis Data Analysis Data Models 52

ODSC - Open Data Science

JANUARY 29, 2024

Using skills such as statistical analysis and data visualization techniques, prompt engineers can assess the effectiveness of different prompts and understand patterns in the responses. This skill focuses on minimizing the resources and time required for an LLM to generate output based on your prompts.

Data Science 52

Data Science Machine Learning Machine Learning AI 52

DagsHub

JULY 25, 2024

Top 10 Deep Learning Platforms The top ten deep-learning platforms that will be driving the market in 2024 are examined in this section. Tutorials Microsoft Azure Machine Learning Microsoft Azure Machine Learning (Azure ML) is a cloud-based platform for building, training, and deploying machine learning models.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

IBM Journey to AI blog

AUGUST 12, 2024

Wearable devices (such as fitness trackers, smart watches and smart rings) alone generated roughly 28 petabytes (28 billion megabytes) of data daily in 2020. And in 2024, global daily data generation surpassed 402 million terabytes (or 402 quintillion bytes). Massive, in fact.

Big Data 111

Big Data Big Data ML ML 111

Towards AI

JUNE 25, 2024

Last Updated on June 25, 2024 by Editorial Team Author(s): Mena Wang, PhD Originally published on Towards AI. Image generated by Gemini Spark is an open-source distributed computing framework for high-speed data processing. This practice vastly enhances the speed of my data preparation for machine learning projects.

ML 80

ML ML EDA Data Wrangling 80

DagsHub

APRIL 21, 2024

A traditional machine learning (ML) pipeline is a collection of various stages that include data collection, data preparation, model training and evaluation, hyperparameter tuning (if needed), model deployment and scaling, monitoring, security and compliance, and CI/CD.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

phData

DECEMBER 4, 2023

This blog was originally written by Erik Hyrkas and updated for 2024 by Justin Delisi This isn’t meant to be a technical how-to guide — most of those details are readily available via a quick Google search — but rather an opinionated review of key processes and potential approaches. authorization server.

Clustering 98

Clustering Database SQL Data Pipeline 98