Towards Data Science

DECEMBER 15, 2023

Having principles around how we think about data retention and usage are important to help guide us in these situations. Institutional Considerations While I am on this topic of data management, I should mention—I recently started a new role! It seems not only reasonable but vital to collect your data and store it!

Machine Learning 90

Machine Learning Data Science Data Security Data Storage 90

Data Engineering Podcast

JUNE 9, 2019

Summary Building a machine learning model can be difficult, but that is only half of the battle. In this episode Stepan Pushkarev, founder of Hydrosphere, explains why deploying and maintaining machine learning projects in production is different from regular software projects and the challenges that they bring.

Machine Learning 100

Machine Learning Management Scala Data Science 100

Data Engineering Podcast

SEPTEMBER 19, 2021

Summary Building, scaling, and maintaining the operational components of a machine learning workflow are all hard problems. Add the work of creating the model itself, and it’s not surprising that a majority of companies that could greatly benefit from machine learning have yet to either put it into production or see the value.

Machine Learning 100

Machine Learning Data Warehouse Banking Metadata 100

Data Engineering Podcast

DECEMBER 11, 2022

Preamble This is a cross-over episode from our new show The Machine Learning Podcast , the show about going from idea to production with machine learning. Summary Data is one of the core ingredients for machine learning, but the format in which it is understandable to humans is not a useful representation for models.

Unstructured Data 100

Unstructured Data Machine Learning Data Engineering Data Engineer 100

Data Engineering Podcast

JANUARY 15, 2022

Summary Data quality control is a requirement for being able to trust the various reports and machine learning models that are relying on the information that you curate. Managing data quality is ostensibly about building trust in your data. Can you describe what Anomalo is and the story behind it?

Machine Learning 100

Machine Learning Management Data Warehouse Data 100

Data Engineering Podcast

JUNE 14, 2021

Summary When you build a machine learning model, the first step is always to load your data. In this episode Paige Roberts explains the benefits of pushing the machine learning processing into the database layer and the approach that Vertica has taken for their implementation. when working within the database?

Machine Learning 100

Machine Learning Database Data Warehouse Hadoop 100

Data Engineering Podcast

FEBRUARY 11, 2019

Summary Machine learning is a class of technologies that promise to revolutionize business. Kevin Dewalt founded Prolego to help Fortune 500 companies build, launch, and maintain their first machine learning projects so that they can remain competitive in our landscape of constant change.

Machine Learning 100

Machine Learning Deep Learning Software Engineer Software Engineering 100

Data Engineering Podcast

AUGUST 6, 2022

For analytical systems there are decades of investment in data warehouses and various modeling techniques. For machine learning applications relational models require additional processing to be directly useful, which is why there has been a growth in the use of vector databases. What are the goals of the project?

Machine Learning 100

Machine Learning Database MySQL PostgreSQL 100

Engineering at Meta

MAY 22, 2024

In recent years, Meta’s data management systems have evolved into a composable architecture that creates interoperability, promotes reusability, and improves engineering efficiency. Data is at the core of every product and service at Meta. Data is at the core of every product and service at Meta.

Data Management 91

Data Management Management Data SQL 91

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. We will learn what it is, why it is important and how Cloudera Machine Learning (CML) is helping organisations tackle this challenge as part of the broader objective of achieving Ethical AI.

Machine Learning 84

Machine Learning Algorithm Government Metadata 84

Data Engineering Podcast

JUNE 15, 2020

Summary Machine learning is a process driven by iteration and experimentation which requires fast and easy access to relevant features of the data being processed. Can you describe what a machine learning feature is? What is StreamSQL and what motivated you to start the business?

Machine Learning 100

Machine Learning Google Cloud Kafka Data Engineering 100

Knowledge Hut

NOVEMBER 18, 2023

Thus, organizations are actively implementing machine learning for IoT models in order to fulfill this need. Convergence of IoT and Machine Learning The need for analyzing high data volumes and automating these tasks to increase their speed and efficiency has led to the convergence of IoT and machine learning.

Machine Learning 52

Machine Learning Transportation Healthcare Medical 52

Knowledge Hut

AUGUST 1, 2023

Ever wondered how machine learning can revolutionize the healthcare industry? Machine learning is a way in which artificial intelligence is used to train algorithms or computers. Machine learning algorithms can analyze potentially tera bytes of data, identify patterns from these data, and make predictions or decisions.

Machine Learning 52

Machine Learning Medical Healthcare Hospitality 52

Knowledge Hut

JUNE 16, 2023

Machine learning is the domain under artificial intelligence, devoted to using algorithms that help machines learn things like humans. The algorithms use historical data as input to predict the outputs until the machine gains human-like proficiency.

Machine Learning 52

Machine Learning Data Mining Algorithm Data Science 52

KDnuggets

JUNE 27, 2023

And how approaches to better data management, version control, and experiment tracking can help build reproducible ML pipelines.

Machine Learning 98

Machine Learning Data Management Building Management 98

Precisely

JULY 18, 2024

Key Takeaways Data Fabric is a modern data architecture that facilitates seamless data access, sharing, and management across an organization. Data management recommendations and data products emerge dynamically from the fabric through automation, activation, and AI/ML analysis of metadata.

Data Management 52

Data Management Management Metadata Database-centric 52

Data Engineering Podcast

AUGUST 14, 2021

In this episode Davit Buniatyan, founder and CEO of Activeloop, explains why he is spending his time and energy on building a platform to simplify the work of getting your unstructured data ready for machine learning. __init__ to learn about the Python language, its community, and the innovative ways it is being used.

Unstructured Data 100

Unstructured Data Machine Learning Data Lake SQL 100

Data Engineering Podcast

APRIL 24, 2022

Summary There are very few tools which are equally useful for data engineers, data scientists, and machine learning engineers. WhyLogs is a powerful library for flexibly instrumenting all of your data systems to understand the entire lifecycle of your data from source to productionized model.

Machine Learning 100

Machine Learning Systems Data Lake Java 100

Data Engineering Podcast

JULY 17, 2022

In this episode Crux CTO Mark Etherington discusses the different costs involved in managing external data, how to think about the total return on investment for your data, and how the Crux platform is architected to reduce the toil involved in managing third party data.

Data Management 130

Data Management Management Metadata MongoDB 130

Data Engineering Podcast

APRIL 19, 2021

Summary Most of the time when you think about a data pipeline or ETL job what comes to mind is a purely mechanistic progression of functions that move data from point A to point B. Sometimes, however, one of those transformations is actually a full-fledged machine learning project in its own right.

Data Pipeline 100

Data Pipeline Machine Learning Data Warehouse Datasets 100

Knowledge Hut

JUNE 20, 2023

A novice data scientist prepared to start a rewarding journey may need clarification on the differences between a data scientist and a machine learning engineer. Many people are learning data science for the first time and need help comprehending the two job positions. They develop self-running software.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Data Engineering Podcast

JUNE 26, 2022

Summary The most complicated part of data engineering is the effort involved in making the raw data fit into the narrative of the business. Master Data Management (MDM) is the process of building consensus around what the information actually means in the context of the business and then shaping the data to match those semantics.

Data Management 100

Data Management Management MongoDB Scala 100

Cloudera

SEPTEMBER 10, 2020

Cloudera has been named a Leader in The Forrester Wave : Notebook-Based Predictive Analytics and Machine Learning, Q3 2020. For enterprise machine learning teams, this means having the right platform, tools, and processes that streamline end-to-end ML to tackle once-impossible business challenges effectively and at scale.

Machine Learning 94

Machine Learning Government Cloud Data Science 94

KDnuggets

JANUARY 11, 2023

Key Data Science, Machine Learning, AI and Analytics Developments of 2022 • Python Matplotlib Cheat Sheets • More Data Science Cheatsheets • Free Data Management with Data Science Learning with CS639 • Data-Driven Holiday Cheer: How Santa is Using Analytics to Make the Season Bright.

Data Science 88

Data Science Machine Learning Python Data 88

Data Engineering Podcast

JUNE 8, 2020

Summary The landscape of data management and processing is rapidly changing and evolving. This is a useful conversation to gain a macro perspective on where businesses are looking to improve their capabilities to work with data. If you hand a book to a new data engineer, what wisdom would you add to it?

Data Management 100

Data Management Management Machine Learning Portfolio 100

AltexSoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Cloudera

NOVEMBER 28, 2023

With its rise in popularity generative AI has emerged as a top CEO priority, and the importance of performant, seamless, and secure data management and analytics solutions to power those AI applications is essential. This means you can expect simpler data management and drastically improved productivity for your business users.

Certification 83

Certification Data Management Management Cloud 83

AltexSoft

MAY 5, 2023

This includes learning, reasoning, problem-solving, perception, language understanding, and decision-making. The key terms that everyone should know within the spectrum of artificial intelligence are machine learning, deep learning, computer vision , and natural language processing. The early adopters, plain and simple.”

Machine Learning 59

Machine Learning Hospitality Algorithm Deep Learning 59

ProjectPro

DECEMBER 16, 2021

Are you a newbie in the data science domain ready to embark on a rewarding journey but are confused between the roles of a Machine Learning Engineer vs Data Scientist? Read this article to understand the significant differences and similarities between a machine learning engineer and a data scientist.

Machine Learning 52

Machine Learning Engineering Pipeline-centric Database-centric 52

KDnuggets

OCTOBER 22, 2019

For full-stack data science mastery, you must understand data management along with all the bells and whistles of machine learning. This high-level overview is a road map for the history and current state of the expansive options for data storage and infrastructure solutions.

Data Management 121

Data Management Management Data Storage Machine Learning 121

Cloudera

SEPTEMBER 14, 2020

When adopting cloud data management, there are some fundamental principles we need to embrace to be successful, or we risk security gaps, failure to maintain regulatory compliance or unexpected cost overruns. Fundamental principles to be successful with Cloud data management. Or so they all claim.

Data Management 111

Data Management Cloud Management Business Analyst 111

Data Engineering Weekly

MARCH 30, 2023

In this episode of Data Engineering Weekly Radio, we delve into modern data stacks under pressure and the potential consolidation of the data industry. We discussed that the siloed nature of many data products has led to industry consolidation, ultimately benefiting customers. Reference [link] [link]

Machine Learning 52

Machine Learning Government AWS Data Engineering 52

KDnuggets

AUGUST 22, 2019

As machine learning evolves, the need for tools and platforms that automate the lifecycle management of training and testing datasets is becoming increasingly important.

Machine Learning 54

Machine Learning Management Data Management Datasets 54

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Management Data Lake Data Warehouse 52

Data Engineering Podcast

MAY 18, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management This episode is supported by Code Comments, an original podcast from Red Hat. The Machine Learning Podcast helps you go from idea to production with machine learning.

Building 278

Building Data Lake High Quality Data Business Intelligence 278