Domino Data Lab

JULY 28, 2021

Data science is an exciting, interdisciplinary field that is revolutionizing the way companies approach every facet of their business. This has led to rapid advancements, as the field’s interdisciplinary nature combines mathematics, statistics, computer science and business knowledge in new and novel ways. Computer Science Skills.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

Domino Data Lab

OCTOBER 7, 2020

Danger of Big Data. Big data is the rage. This could be lots of rows (samples) and few columns (variables) like credit card transaction data, or lots of columns (variables) and few rows (samples) like genomic sequencing in life sciences research. Statistical methods for analyzing this two-dimensional data exist.

Statistics 145

Statistics Testing Predictive Modeling Modeling 145

IBM Big Data Hub

FEBRUARY 13, 2024

Generative AI represents a significant advancement in deep learning and AI development, with some suggesting it’s a move towards developing “ strong AI.” Generative AI uses advanced machine learning algorithms and techniques to analyze patterns and build statistical models.

Enterprise 127

Enterprise Modeling Testing Data-driven 127

IBM Big Data Hub

NOVEMBER 29, 2023

They are already identifying and exploring several real-life use cases for synthetic data, such as: Generating synthetic tabular data to increase sample size and edge cases. You can combine this data with real datasets to improve AI model training and predictive accuracy. How to get started with synthetic data in watsonx.ai

Metrics 87

Metrics Machine Learning Risk Statistics 87

Smart Data Collective

AUGUST 20, 2021

As we said in the past, big data and machine learning technology can be invaluable in the realm of software development. Machine learning technology has become a lot more important in the app development profession. You need to know how to leverage machine learning algorithms appropriately.

Machine Learning 89

Machine Learning Data mining Advertising Deep Learning 89

IBM Big Data Hub

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects.

Data Science 59

Data Science Machine Learning Cost-Benefit Deep Learning 59

IBM Big Data Hub

APRIL 18, 2024

LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language. Building an in-house team with AI, deep learning , machine learning (ML) and data science skills is a strategic move. What are the types of AGI?

Cost-Benefit 96

Cost-Benefit Modeling Manufacturing Interactive 96

Domino Data Lab

JULY 28, 2021

Data science is a field at the convergence of statistics, computer science and business. In this article, take a deep dive into data science and how Domino’s Enterprise MLOps platform allows you to scale data science in your business. What is Data Science and How is it Used? What are Data Scientists?

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

Smart Data Collective

OCTOBER 14, 2019

Regardless of if you’re a data science professional or an IT department who wants to help your company have more successful data science projects, it’s essential to have some data science tools under your belt to avail of when needed. In short, it makes big data analysis more accessible.

Data Science 69

Data Science Machine Learning Big Data Interactive 69

Domino Data Lab

JULY 15, 2021

Key categories of tools and a few examples include: Data Sources. Data sources used by data scientists are nearly endless. SQL based) to big data stores (e.g. R is a programming language used for a wide variety of data science tasks, with its capabilities being extended through packages and different IDEs.

Data Science 145

Data Science Visualization Modeling Enterprise 145

Domino Data Lab

MAY 8, 2019

For example, in the case of more recent deep learning work, a complete explanation might be possible: it might also entail an incomprehensible number of parameters. They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

JUNE 23, 2019

Be aware that machine learning often involves working on something that isn’t guaranteed to work. As a result, Skomoroch advocates getting “designers and data scientists, machine learning folks together and using real data and prototyping and testing” as quickly as possible. Testing is critical. Transcript.

Management 110

Management Machine Learning Experimentation Metrics 110

Domino Data Lab

MARCH 3, 2019

Over the past six months, Ben Lorica and I have conducted three surveys about “ABC” (AI, Big Data, Cloud) adoption in enterprise. O’Reilly Media published our analysis as free mini-books: The State of Machine Learning Adoption in the Enterprise (Aug 2018). The data types used in deep learning are interesting.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

O'Reilly on Data

MAY 21, 2019

Consider deep learning, a specific form of machine learning that resurfaced in 2011/2012 due to record-setting models in speech and computer vision. Machine learning is not only appearing in more products and systems, but as we noted in a previous post , ML will also change how applications themselves get built in the future.

Machine Learning 238

Machine Learning Technology Deep Learning Data Science 238

Smart Data Collective

NOVEMBER 9, 2022

There are a number of great applications of machine learning. One of the biggest benefits is testing processes for optimal effectiveness. The main purpose of machine learning is to partially or completely replace manual testing. One example is using machine learning tools like Selenium to test web development processes.

Machine Learning 99

Machine Learning Testing Cost-Benefit Data-driven 99

O'Reilly on Data

MARCH 24, 2020

However, attempting to repurpose pre-existing data can muddy the water by shifting the semantics from why the data was collected to the question you hope to answer. ” One of his more egregious errors was to continually test already collected data for new hypotheses until one stuck, after his initial hypothesis failed [4]. .”

Machine Learning 346

Machine Learning Statistics Data Quality Modeling 346

O'Reilly on Data

JANUARY 25, 2021

Both SRE and DevOps emphasize similar practices: version control (62% growth for GitHub, and 48% for Git), testing (high usage, though no year-over-year growth), continuous deployment (down 20%), monitoring (up 9%), and observability (up 128%). AI breaks these assumptions because data is more important than code.

Machine Learning 363

Machine Learning Software Testing Technology 363

Smart Data Collective

MAY 19, 2021

Big data technology has become a major disrupting factor in the energy industry. Many energy conglomerates have started embracing data analytics to expand their markets, respond to new trends, streamline operations and bolster efficiency. The clean energy sector has not been untouched by the big data revolution.

Data Analytics 90

Data Analytics Analytics Big Data Predictive Analytics 90