O'Reilly Media - Ideas

JUNE 5, 2019

Get hands-on training in Docker, microservices, cloud native, Python, machine learning, and many other topics. Learn new topics and refine your skills with more than 219 new live online training courses we opened up for June and July on the O'Reilly online learning platform. AI and machine learning.

Course 51

Course Training Artificial Inteligence Software Review 51

O'Reilly Media - Ideas

MARCH 1, 2023

Content about software development was the most widely used (31% of all usage in 2022), which includes software architecture and programming languages. Software development is followed by IT operations (18%), which includes cloud, and by data (17%), which includes machine learning and artificial intelligence.

Trends 137

Trends Technical Review Technology Software Review 137

Apiumhub

APRIL 1, 2021

Learning data science through books will help you get a holistic view of Data Science as data science is not just about computing, it also includes mathematics, probability, statistics, programming, machine learning, and much more. Top Data science books you should definitely read.

Artificial Inteligence 52

Artificial Inteligence Data Handbook Machine Learning 52

Cloudera

DECEMBER 21, 2020

Company data exists in the data lake. Data Catalog profilers have been run on existing databases in the Data Lake. A Cloudera Machine Learning Workspace exists . A Cloudera Data Warehouse virtual warehouse with Cloudera Data Visualisation enabled exists. The Data Scientist. The KPI is 0.5

Data 97

Data Virtualization Banking Data Engineering 97

Altexsoft

FEBRUARY 8, 2021

To support the planning process, predictive analytics and machine learning (ML) techniques can be implemented. We have previously described demand forecasting methods and the role of machine learning solutions in a dedicated article. Today, consumers’ preferences are changing momentarily and often chaotically.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Altexsoft

JANUARY 14, 2021

Snowflake, Redshift, BigQuery, and Others: Cloud Data Warehouse Tools Compared. From simple mechanisms for holding data like punch cards and paper tapes to real-time data processing systems like Hadoop, data storage systems have come a long way to become what they are now. Cloud data warehouse architecture.

Backup 115

Backup Azure Software Review Systems Review 115

Apiumhub

AUGUST 12, 2021

This year you will have 6 unique tracks: Cloud Computing: IaaS, PaaS, SaaS DevOps: Microservices, Automation, ASRs Cybersecurity: Threats, Defenses, Tests Data Science: ML, AI, Big Data, Business Analytics Programming languages: C++, Python, Java, Javascript,Net Future & Inspire: Mobility, 5G data networks, Diversity, Blockchain, VR.

Industry 59

Industry Technical Advisors CTO Coach Azure 59

Altexsoft

JANUARY 26, 2022

In recent years, it’s getting more common to see organizations looking for a mysterious analytics engineer. As you may guess from the name, this role sits somewhere in the middle of a data analyst and data engineer, but it’s really neither one nor the other. Here’s the video explaining how data engineers work.

Analytics 59

Analytics Engineering Data Engineering Software Engineering 59

O'Reilly Media - Ideas

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.

Conference 8

Conference Data Data Engineering Artificial Inteligence 8

Cloudera

NOVEMBER 2, 2020

These include stream processing/analytics, batch processing, tiered storage (i.e. for active archive or joining live data with historical data), or machine learning. Architecture for Real-Time Data Warehousing with Extended Capabilities. Analytics storage and query engine for pre-aggregated event data.

Data 91

Data Analytics Storage Big Data 91

Cloudera

FEBRUARY 22, 2021

This category describes the unique ability of CDP to accelerate deployment of use cases (and, as a result, the associated business value) by: . CDP helps clients reduce (or avoid entirely) costs for ancillary technology tools that are used in conjunction with competing analytical solutions. query failures, cost overruns).

Data 78

Data Analytics Government Technical Review 78