Domino Data Lab

JULY 15, 2021

Originally created for software development, Python is used in a variety of contexts, including deep learning research and model deployment. RStudio is an IDE for the R language used primarily for statistical analysis as well as data visualization. Some common IDEs are RStudio and Jupyter Notebook.

Data Science 145

Data Science Visualization Modeling Enterprise 145

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 drawback of GAMs is that they do not allow feature interactions. linear regression, trees) can be too rigid in their functional forms.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

FineReport

DECEMBER 19, 2019

At the same time, it also advocates visual exploratory analysis. The visualization component library of FineReport is very rich. In addition, Jupyter Notebook is also an excellent interactive tool for data analysis and provides a convenient experimental platform for beginners. It is recommended that everyone learn to learn.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

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. The AGI research field is constantly evolving.

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

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

DataRobot Blog

MAY 26, 2022

These methods provided the benefit of being supported by rich literature on the relevant statistical tests to confirm the model’s validity—if a validator wanted to confirm that the input predictors of a regression model were indeed relevant to the response, they need only to construct a hypothesis test to validate the input.

Risk 52

Risk Modeling Metrics Business Objectives 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

JULY 9, 2019

Here is a picture of The New York Times on its birthday in 1851, and for the vast majority of its lifespan this is pretty much what the user experience of interacting with The New York Times looks like. It’s a visual problem so it works both in our MSE and it works by your eyeballs. And it works. We crowdsourced it.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

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

IBM Big Data Hub

OCTOBER 12, 2023

Early iterations of the AI applications we interact with most today were built on traditional machine learning models. These models rely on learning algorithms that are developed and maintained by data scientists. Due to deep learning and other advancements, the field of AI remains in a constant and fast-paced state of flux.

Machine Learning 74

Machine Learning Deep Learning Interactive Modeling 74

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 81

Machine Learning Modeling Deep Learning Predictive Modeling 81

O'Reilly on Data

FEBRUARY 18, 2020

After several years of steady climbing—and after outstripping Java in 2017—Python-related interactions now comprise almost 10% of all usage. As statistics and related techniques become more important in software development, more programmers are encountering stats in programming classes. We combine them here for simplicity’s sake.

Data-driven 335

Data-driven Software Statistics Marketing 335

Domino Data Lab

JUNE 23, 2019

This talk will describe how you can navigate all these challenges that you’re going to face and build a business where every product interaction benefits from your investment in machine learning. It used deep learning to build an automated question answering system and a knowledge base based on that information.

Management 110

Management Machine Learning Experimentation Metrics 110

Smart Data Collective

OCTOBER 14, 2019

Ludwig is a tool that allows people to build data-based deep learning models to make predictions. It allows secure and interactive SQL analytics at the petabyte scale. Paraview helps you analyze your data with qualitative or quantitative techniques, then get another perspective on it with visualizations.

Data Science 67

Data Science Machine Learning Big Data Interactive 67