CIO Business Intelligence

APRIL 25, 2022

The course includes instruction in statistics, machine learning, natural language processing, deep learning, Python, and R. The course culminates in a final data project in collaboration with real-world industry professionals. Cost: €4,995 to €5,595 for the full-stack data science program; €1,295 for data essentials.

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

Smart Data Collective

MAY 17, 2021

Big data is at the heart of the digital revolution. Basing fleet management operations on data is not new, and in some ways, it’s always been a part of the industry. Basing fleet management operations on data is not new, and in some ways, it’s always been a part of the industry. Organizations have already realized this.

Big Data 101

Big Data Cost-Benefit IoT Machine Learning 101

Rocket-Powered Data Science

JULY 6, 2021

Customer purchase patterns, supply chain, inventory, and logistics represent just a few domains where we see new and emergent behaviors, responses, and outcomes represented in our data and in our predictive models. 7) Deep learning (DL) may not be “the one algorithm to dominate all others” after all.

Data-driven 279

Data-driven Machine Learning IoT Deep Learning 279

Alation

APRIL 14, 2022

A cloud environment with such features will support collaboration across departments and across common data types, including csv, JSON, XML, AVRO, Parquet, Hyper, TDE, and more. It’s More Important to Know What Your Data Means Than Where It Is.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena. 221) to 2019 (No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

O'Reilly on Data

MARCH 24, 2020

No data analysts/scientists work on this data pipeline as everything must happen in real time, requiring an automated data preparation and data quality workflow (e.g., The third point above speaks more generally to the need for automation around all parts of the data science workflow.

Machine Learning 346

Machine Learning Statistics Data Quality Modeling 346