Domino Data Lab

JULY 28, 2021

Through a marriage of traditional statistics with fast-paced, code-first computer science doctrine and business acumen, data science teams can solve problems with more accuracy and precision than ever before, especially when combined with soft skills in creativity and communication. Math and Statistics Expertise.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

Smarten

APRIL 19, 2024

Benefits include customized and optimized models, data, parameters and tuning. Price and bundling optimization, demand pricing, and other variables will be included to provide the best options, prices and responses and to personalize the approach and present results for data analysis and for end users.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

IBM Big Data Hub

JULY 6, 2023

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. Ultimately, data science is used in defining new business problems that machine learning techniques and statistical analysis can then help solve. appeared first on IBM Blog.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

Smart Data Collective

NOVEMBER 1, 2020

With that being said, let’s have a closer look at how unsupervised machine learning is omnipresent in all industries. What Is Unsupervised Machine Learning? If you’ve ever come across deep learning, you might have heard about two methods to teach machines: supervised and unsupervised. We have, and it’s a hell of a task.

Machine Learning 134

Machine Learning Data mining Visualization Statistics 134

Smart Data Collective

SEPTEMBER 16, 2020

These statistical models are growing as a result of the wide swaths of available current data as well as the advent of capable artificial intelligence and machine learning. While third-party data can play a role in both optimization and conversions, it isn’t necessarily the most useful in the predictive analytics world.

Predictive Analytics 122

Predictive Analytics Analytics Predictive Modeling Data mining 122

FineReport

DECEMBER 19, 2019

At the same time, it also advocates visual exploratory analysis. The visualization component library of FineReport is very rich. Pandas incorporates a large number of analysis function methods, as well as common statistical models and visualization processing. It is recommended that everyone learn to learn.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

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. In fact, deep learning was first described theoretically in 1943.

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

On the one hand, basic statistical models (e.g. On the other hand, sophisticated machine learning models are flexible in their form but not easy to control. The first is that they are straightforward to optimize using traditional gradient-based optimizers as long as we pre-specify the placement of the knots.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

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. MLOps and IBM Watsonx.ai

Data Science 53

Data Science Machine Learning Cost-Benefit Deep Learning 53

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.

Cost-Benefit 89

Cost-Benefit Modeling Manufacturing Interactive 89

datapine

NOVEMBER 19, 2019

Exciting and futuristic, the concept of computer vision is based on computing devices or programs gaining the ability to extract detailed information from visual images. Visual analytics: Around three million images are uploaded to social media every single day. Artificial Intelligence (AI).

Technology 279

Technology Internet of Things IT IoT 279

O'Reilly on Data

FEBRUARY 18, 2020

Usage specific to Python as a programming language grew by just 4% in 2019; by contrast, usage that had to do with Python and ML—be it in the context of AI, deep learning, and natural language processing, or in combination with any of several popular ML/AI frameworks—grew by 9%. 3] ML and AI aren’t in any sense the same thing, either.

Data-driven 342

Data-driven Software Statistics Marketing 342

bridgei2i

OCTOBER 7, 2020

Importance of capturing market data for optimized pricing models. Underwriting essentially means evaluating the risk proposition of an insurance cover and determining how much an insurer should charge for the same by studying historical data and statistical models. The way ahead for insurers.

Insurance 52

Insurance Sales Strategy Digital Transformation 52

Domino Data Lab

MAY 8, 2019

On the other hand, as Lipton emphasized, while the tooling produces interesting visualizations, visualizations do not imply interpretation. ML model interpretability and data visualization. From my experiences leading data teams, when a business is facing difficult challenges, data visualizations can help or hurt.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

MARCH 3, 2019

O’Reilly Media had an earlier survey about deep learning tools which showed the top three frameworks to be TensorFlow (61% of all respondents), Keras (25%), and PyTorch (20%)—and note that Keras in this case is likely used as an abstraction layer atop TensorFlow. The data types used in deep learning are interesting.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Domino Data Lab

JULY 9, 2019

or are you looking for me to help you decide on what is the optimal treatment in order to get the outcome you want?” You really want…you really already know what actions you want to perform and you want me to help you figure out what’s the optimal treatment, not what’s going to happen in the absence of treatment.”

Data Science 112

Data Science Machine Learning Advertising Modeling 112

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. He also really informed a lot of the early thinking about data visualization. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. You can take TensorFlow.js

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

IBM Big Data Hub

DECEMBER 20, 2023

ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions. A semi-supervised learning model might use unsupervised learning to identify data clusters and then use supervised learning to label the clusters.

Machine Learning 74

Machine Learning Modeling Deep Learning Predictive Modeling 74

Domino Data Lab

JUNE 23, 2019

It used deep learning to build an automated question answering system and a knowledge base based on that information. Google, Facebook, other leaders, they really have set up a culture of extreme measurement where every part of their product experience is instrumented to optimize clicks and drive user engagement.

Management 110

Management Machine Learning Experimentation Metrics 110

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. Machine learning is used in many industries. It is headquartered in Silicon Valley.

Machine Learning 97

Machine Learning Testing Cost-Benefit Data-driven 97