IBM Journey to AI blog

JULY 6, 2023

Just as humans can learn through experience rather than merely following instructions, machines can learn by applying tools to data analysis. Machine learning works on a known problem with tools and techniques, creating algorithms that let a machine learn from data through experience and with minimal human intervention.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

Pickl AI

JULY 25, 2023

They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Alation

FEBRUARY 13, 2020

By matching landmarks on the human face or identifying patterns in speech rate, pitch range, intensity, and voice quality, AI is able to detect human emotions — some algorithms can even detect 10-different emotions. AI is not a fad, algorithmic decision-making is inevitable. Human Curation + Machine Learning.

Machine Learning 52

Machine Learning Machine Learning Analytics Analytics 52

Women in Big Data

SEPTEMBER 7, 2024

The real advantage of big data lies not just in the sheer quantity of information but in the ability to process it in real-time. Variety Data comes in a myriad of formats including text, images, videos, and more. Veracity Veracity relates to the accuracy and trustworthiness of the data.

Big Data 59

Big Data Big Data Database Machine Learning 59

IBM Journey to AI blog

SEPTEMBER 25, 2023

With a few taps on a mobile device, riders request a ride; then, Uber’s algorithms work to match them with the nearest available driver and calculate the optimal price. It can ingest data from offline batch data sources (such as Hadoop and flat files) as well as online data sources (such as Kafka).

Data Lakes 102

Data Lakes Analytics Analytics Clustering 102

Pickl AI

JANUARY 28, 2025

This involves several key processes: Extract, Transform, Load (ETL): The ETL process extracts data from different sources, transforms it into a suitable format by cleaning and enriching it, and then loads it into a data warehouse or data lake. Data Lakes: These store raw, unprocessed data in its original format.

Business Intelligence 52

Business Intelligence Business Intelligence ETL Data Lakes 52

Pickl AI

APRIL 6, 2023

In-depth knowledge of distributed systems like Hadoop and Spart, along with computing platforms like Azure and AWS. Having a solid understanding of ML principles and practical knowledge of statistics, algorithms, and mathematics. Which service would you use to create Data Warehouse in Azure?

Azure 52

Azure Data Engineering Data Engineering Data Engineering 52

Pickl AI

JULY 8, 2024

NoSQL Databases: Flexible, scalable solutions for unstructured or semi-structured data. Data Warehouses : Centralised repositories optimised for analytics and reporting. Data Lakes : Scalable storage for raw and processed data, supporting diverse data types.

Data Pipeline 52

Data Pipeline Data Quality Database Apache Kafka 52

DagsHub

NOVEMBER 11, 2024

We use data-specific preprocessing and ML algorithms suited to each modality to filter out noise and inconsistencies in unstructured data. NLP cleans and refines content for text data, while audio data benefits from signal processing to remove background noise. Such algorithms are key to enhancing data.

AI 52

AI AI Data Lakes Database 52