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 49

Course Training Artificial Inteligence Software Review 49

O'Reilly Media - Ideas

MAY 1, 2019

Get hands-on training in machine learning, blockchain, cloud native, PySpark, Kubernetes, and many other topics. Learn new topics and refine your skills with more than 160 new live online training courses we opened up for May and June on the O'Reilly online learning platform. AI and machine learning.

Course 45

Course Training Artificial Inteligence Machine Learning 45

Altexsoft

FEBRUARY 11, 2023

The 11th annual survey of Chief Data Officers (CDOs) and Chief Data and Analytics Officers reveals 82 percent of organizations are planning to increase their investments in data modernization in 2023. What’s more, investing in data products, as well as in AI and machine learning was clearly indicated as a priority.

Data 87

Data Data Engineering Big Data Architecture 87

Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data 91

Data Analytics Open Source Architecture 91

Cloudera

FEBRUARY 25, 2021

Cloudera has a front-row seat to organizational challenges as those enterprises make Machine Learning a core part of their strategies and businesses. The work of a machine learning model developer is highly complex. We work with the largest companies in the world to help tackle their most challenging ML problems.

Machine Learning 82

Machine Learning Artificial Inteligence Telecommunications Enterprise 82

Apiumhub

JUNE 22, 2021

Data Innovation Summit topics. Data Innovation Summit is here to help you hear cutting-edge content, meet and engage with peers and find solutions to your most pressing challenges. Focus on Data-Ops, ML Ops, Auto ML, Cloud ML, Fast Data, data pipeline, data lineage, modeling, data flow monitoring, feature extraction and much more.

Innovation 84

Innovation Data Technical Review Artificial Inteligence 84

O'Reilly Media - Ideas

JULY 1, 2019

But we are also beginning to see AI and machine learning gain traction in areas like customer service and IT. One area I’m particularly interested in is the application of AI and automation technologies in data science, data engineering, and software development. numpy, TensorFlow, etc.).

Software Development 61

Software Development Artificial Inteligence Software Machine Learning 61

O'Reilly Media - Ideas

FEBRUARY 11, 2019

Highlights and use cases from companies that are building the technologies needed to sustain their use of analytics and machine learning. In a forthcoming survey, “Evolving Data Infrastructure,” we found strong interest in machine learning (ML) among respondents across geographic regions. Deep Learning.

Big Data 86

Big Data Technology Tools Cloud 86

Mobilunity

MAY 8, 2023

It is designed to store vast amounts of data from a variety of sources. Moreover an Enterprise Data Lake makes it accessible to data scientists, analysts, and other users across the enterprise. Ingestion zone is where data is collected from various sources and ingested into the data lake.

Engineering 52

Engineering Data Storage AWS 52

Capgemini

JANUARY 17, 2023

Here are four resolutions to make your data strategy pay off this year. Reassess your data architecture. Most executives (72 percent) say that data, both fragmented and with poor quality, is likely to be the biggest issue when aspiring to achieve AI goals. Stay the course to be prepared for a happy new year!

Strategy 52

Strategy Technical Review Data Artificial Inteligence 52

Altexsoft

OCTOBER 30, 2021

If you’re an executive who has a hard time understanding the underlying processes of data science and get confused with terminology, keep reading. We will try to answer your questions and explain how two critical data jobs are different and where they overlap. Data science vs data engineering.

Data Engineering 98

Data Engineering Engineering Data Machine Learning 98

DataRobot

MARCH 10, 2022

With Snowflake’s newest feature release, Snowpark , developers can now quickly build and scale data-driven pipelines and applications in their programming language of choice, taking full advantage of Snowflake’s highly performant and scalable processing engine that accelerates the traditional data engineering and machine learning life cycles.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning IoT 52

O'Reilly Media - Ideas

MARCH 6, 2019

Get hands-on training in machine learning, AWS, Kubernetes, Python, Java, and many other topics. Learn new topics and refine your skills with more than 170 new live online training courses we opened up for March and April on the O'Reilly online learning platform. AI and machine learning. Blockchain.

Course 10

Course Artificial Inteligence Training Microservices 10

Erik Bernhardsson

OCTOBER 27, 2015

There’s no clear problem formulation, no clear loss function, lots of various data sets to use. Of course you’re going to waste too much time doing something that turns out to nothing. Learning stuff is what matters and kind of by definition you have to do stupid s**t before you learned it. But research is that way.

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Erik Bernhardsson

OCTOBER 27, 2015

There’s no clear problem formulation, no clear loss function, lots of various data sets to use. Of course you’re going to waste too much time doing something that turns out to nothing. Learning stuff is what matters and kind of by definition you have to do stupid s**t before you learned it. But research is that way.

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Existek

SEPTEMBER 28, 2023

Developers often have specialized roles based on their areas of expertise, like machine learning, computer vision, natural language processing, deep learning, robotics process automation, etc. Developers often work with data acquisition, data cleaning, data transformation, and data augmentation.

Artificial Inteligence 52

Artificial Inteligence Development How To Artificial Intelligence 52

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

High Scalability

APRIL 14, 2020

You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc. Learn how to train interviewers so everyone's on the same page.

Education 42

Education System Design Scalability Software Engineering 42

High Scalability

MAY 12, 2020

You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc. Learn how to train interviewers so everyone's on the same page.

Education 41

Education System Design Scalability Software Engineering 41

Altexsoft

AUGUST 25, 2020

Big data can be quite a confusing concept to grasp. What to consider big data and what is not so big data? Big data is still data, of course. But it requires a different engineering approach and not just because of its amount. Data engineering vs big data engineering.

Big Data 75

Big Data Data Engineering Engineering Data 75

High Scalability

APRIL 28, 2020

You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc. Learn how to train interviewers so everyone's on the same page.

Education 41

Education System Design Scalability Software Engineering 41

Altexsoft

APRIL 13, 2023

But of course, you can only share data you have yourself – so higher visibility leads to higher transparency. Supply chain control tower architecture: main components, integrations, and data sources As we mentioned, an SCCT is typically comprised of multiple components that handle various aspects of supply chain management.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

High Scalability

MAY 26, 2020

You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc. Learn the Good Parts of AWS. Please apply here.

Education 40

Education System Design AWS Scalability 40

Apiumhub

AUGUST 12, 2021

Gema Parreño Piqueras – Lead Data Science @Apiumhub Gema Parreno is currently a Lead Data Scientist at Apiumhub, passionate about machine learning and video games, with three years of experience at BBVA and later at Google in ML Prototype. Twitter: [link] Linkedin: [link]. Twitter: ??

Industry 59

Industry Technical Advisors CTO Coach Azure 59

O'Reilly Media - Ideas

JULY 28, 2020

It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Trends and tools in AutoML and Deep Learning have certainly reduced the time, skills, and effort required to build a prototype, if not an actual product. Data Quality and Standardization.

Marketing 145

Marketing Weak Development Team Metrics UI/UX 145

O'Reilly Media - Ideas

FEBRUARY 18, 2020

This year’s growth in Python usage was buoyed by its increasing popularity among data scientists and machine learning (ML) and artificial intelligence (AI) engineers. Software architecture, infrastructure, and operations are each changing rapidly. Trends in software architecture, infrastructure, and operations.

Technical Review 139

Technical Review Microservices Data Engineering Architecture 139

Cloudera

OCTOBER 1, 2022

These companies face a unique set of data governance challenges regarding infrastructure and compliance on local, national, and international levels. Some organizations are choosing to confront these challenges with the help of tools like machine learning (ML) and artificial intelligence (AI) to automate, streamline, and scale compliance. .

Government 73

Government Artificial Inteligence Enterprise Strategy 73

Altexsoft

SEPTEMBER 9, 2022

It aims at making data assets understandable and discoverable for users. In our library analogy, metadata management (in its simplest form, of course) would involve creating a book catalog and a user guide to navigate visitors around. Alation supports active metadata management with its Data Governance App and Data Catalog tools.

Tools 59

Tools Technical Review Software Review Systems Review 59

Altexsoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Traditional data warehouse platform architecture. Data lake. Data lake architecture example.

Architecture 52

Architecture Data Storage Machine Learning 52

O'Reilly Media - Ideas

JANUARY 25, 2024

While we like to talk about how fast technology moves, internet time, and all that, in reality the last major new idea in software architecture was microservices, which dates to roughly 2015. Who wants to learn about coding practices when you’re letting GitHub Copilot write your code for you? This has been a strange year.

Trends 116

Trends Technical Review Technology Artificial Inteligence 116

Altexsoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general. How data engineering works in a nutshell.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

ParkMyCloud

JANUARY 17, 2020

Display a basic understanding of core AWS services, uses, and basic AWS architecture best practices. Design and maintain network architecture for all AWS services. AWS Certified Big Data – Speciality. For individuals who perform complex Big Data analyses and have at least two years of experience using AWS.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

O'Reilly Media - Ideas

FEBRUARY 11, 2020

Key survey results: The C-suite is engaged with data quality. Data scientists and analysts, data engineers, and the people who manage them comprise 40% of the audience; developers and their managers, about 22%. Data quality might get worse before it gets better. Adopting AI can help data quality.

Weak Development Team 127

Weak Development Team Data Technical Review Survey 127

Altexsoft

NOVEMBER 7, 2022

You can hardly compare data engineering toil with something as easy as breathing or as fast as the wind. The platform went live in 2015 at Airbnb, the biggest home-sharing and vacation rental site, as an orchestrator for increasingly complex data pipelines. How data engineering works. Airflow architecture.

Weak Development Team 52

Weak Development Team Technical Review Software Review Systems Review 52

Altexsoft

OCTOBER 24, 2019

We will define how enterprise warehouses are different from the usual ones, what types of data warehouses exist, and how they work. The focus of this material is to provide information about the business value of each architectural and conceptual approach to building a warehouse. What is an Enterprise Data Warehouse?

Architecture 50

Architecture Enterprise Data Technical Review 50

Apiumhub

APRIL 5, 2022

M2- Data Engineering Stage: Technical track focusing on agile approaches to designing, implementing and maintaining a distributed data architecture to support a wide range of tools and frameworks in production. Workshops: Several rooms for short workshops and crash-courses.

Innovation 52

Innovation Data Artificial Inteligence Case Study 52

BPM

JANUARY 18, 2019

Now we’re seeing AI dominating the conversations (without a lot of actual adoption in the early majority), and RPA creating a lot of buzz, though companies adopting it are starting to realize that scaling an RPA based automation architecture is flawed by design. This requires a new architecture capable of true scale and speed.

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111