IBM Big Data Hub

DECEMBER 15, 2023

PyTorch is an open-source AI framework offering an intuitive interface that enables easier debugging and a more flexible approach to building deep learning models. It is a popular choice among researchers and developers for rapid software development prototyping and AI and deep learning research.

Deep Learning 69

Deep Learning Experimentation Machine Learning Risk 69

Cloudera

FEBRUARY 25, 2021

The work of a machine learning model developer is highly complex. They need strong data exploration and visualization skills, as well as sufficient data engineering chops to fix the gaps they find in their initial study. Here’s a preview of what you can leverage with one click in CML: Deep Learning for Anomaly Detection.

Deep Learning 81

Deep Learning Machine Learning Forecasting Visualization 81

CIO Business Intelligence

SEPTEMBER 19, 2023

At Estée Lauder , the company has released a voice-enabled makeup assistant designed to assist visually impaired people with applying makeup. AI personalization utilizes data, customer engagement, deep learning, natural language processing, machine learning, and more to curate highly tailored experiences to end-users and customers.

Enterprise 141

Enterprise Cost-Benefit Optimization Deep Learning 141

datapine

AUGUST 14, 2019

To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations. provides the user with visualizations, code editor, and debugging. Let’s get started. Exclusive Bonus Content: Download Our Free Data & Science Checklist!

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

CIO Business Intelligence

JUNE 22, 2022

In the face of emerging and disruptive technology, there is a need to transform your business processes and your interaction with your customers digitally. Drive insight with data-driven visualization. To learn more, click here. This is the essence of digital transformation — to become a digital leader. IT Leadership

Digital Transformation 101

Digital Transformation Visualization Technology Marketing 101

IBM Big Data Hub

APRIL 18, 2024

Building an in-house team with AI, deep learning , machine learning (ML) and data science skills is a strategic move. Also, its emotional intelligence allows it to adapt communication to be empathetic and supportive, creating a more positive interaction for the customer. The AGI research field is constantly evolving.

Cost-Benefit 88

Cost-Benefit Modeling Manufacturing Interactive 88

Jet Global

AUGUST 24, 2020

iVEDiX helps harness, understand and use that data with its configurable IOT engine, powerful configuration tools and an imaginatively interactive visualization platform. iVEDiX has delivered brilliantly curated digital solutions for some of the world’s most progressive organizations.

IoT 80

IoT Analytics Deep Learning Digital Transformation 80

Analytics Vidhya

MARCH 15, 2023

One of the most notable breakthroughs is ChatGPT, which is designed to interact with users through conversations, maintain the context, handle follow-up questions, and correct itself. However, ChatGPT is limited in processing visual information since it’s trained with a single language modality.

Visualization 323

Visualization Interactive Modeling Analytics 323

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

DataRobot

OCTOBER 20, 2021

Individuals interacting with AI systems should possess a baseline data literacy, especially in high-risk use cases that require human collaboration at the final decision-making stage. Data literacy is the ability to understand data science and AI applications critically using basic data visualization, communication, and reasoning skills.

Machine Learning 52

Machine Learning Metrics Risk Deep Learning 52

Domino Data Lab

JULY 28, 2021

Data scientists have to work with different types of data, interact with different types of computer systems, program in various languages, work in different development environments and stitch all of their work together across the entire data science lifecycle. Computer Science Skills. After cleaning, the data is now ready for processing.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

AWS Big Data

JUNE 26, 2023

We use Amazon Neptune to visualize the customer data before and after the merge and harmonization. We use Neptune to visualize the customer data before and after the merge and harmonization to see how the transform FindMacthes can bring all related customer data together to get a complete customer 360 view.

Insurance 76

Insurance Visualization Data Lake Metrics 76

Insight

MAY 16, 2019

It is a high-level, multifaceted field that allows machines to iteratively learn and understand complex representations from images and videos to automate human visual tasks. Pinterest developed a visual search engine which uses an object detection pipeline for content recommendation.

Deep Learning 84

Deep Learning Machine Learning Metadata Data Science 84

Jen Stirrup

MAY 5, 2020

You can use Visual Studio, which is a home for many developers. You can also use familiar languages, such as Python, R, Scala, JavaScript and code in Visual Studio. Apache Spark also allows you to do Machine Learning, streaming analytics, interactive querying, and also data visualization, as well.

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

bridgei2i

DECEMBER 15, 2021

With significant adoption among industries as well as personal lives, AI is impacting enterprise transformation at scale, whilst changing the way humans interact with machines. Videos uploaded on streaming sites usually include detailed information about the visuals such as descriptions, emotions, and nature of the show.

Recreation/Entertainment 52

Recreation/Entertainment Metadata Advertising Predictive Modeling 52

Domino Data Lab

JULY 28, 2021

Today, data is generated constantly through multiple channels including transactional systems, sensors, cameras, and online interactions. In fact, deep learning was first described theoretically in 1943. Improvements in storage have made it possible to capture, manage and use this data in as fast as real time.

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

DataRobot Blog

MAY 26, 2022

However, with the widespread adoption of modern ML techniques, including gradient-boosted decision trees (GBDTs) and deep learning algorithms , many traditional validation techniques become difficult or impossible to apply.

Risk 52

Risk Modeling Metrics Business Objectives 52

Domino Data Lab

AUGUST 22, 2019

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. Introduction.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

TF Lattice offers semantic regularizers that can be applied to models of varying complexity, from simple Generalized Additive Models, to flexible fully interacting models called lattices, to deep models that mix in arbitrary TF and Keras layers. The drawback of GAMs is that they do not allow feature interactions.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

AWS Big Data

MARCH 1, 2023

Finally, to interact with and visualize results from our solution, we build an interactive Streamlit web application running on AWS Fargate. Finally, an interactive Streamlit web application is deployed with Fargate. Taylor McNally is a Deep Learning Architect at Amazon Machine Learning Solutions Lab.

Data Lake 81

Data Lake Deep Learning Modeling Interactive 81

Cloudera

OCTOBER 26, 2022

Deep Learning for Anomaly Detection : ?? Apply modern, deep learning techniques for anomaly detection to identify network intrusions. Deep Learning for Image Analysis : Build a semantic search application with deep learning models. AMPs so far include: .

Machine Learning 74

Machine Learning Deep Learning Cost-Benefit Forecasting 74

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 72

Machine Learning Deep Learning Interactive Modeling 72

Smarten

APRIL 19, 2024

Vendors, service providers and analytics solution companies will package data products and design data management solutions to support business users in their interaction with suppliers, customers and stakeholders, and to inform and support customers and end users as they choose products and options.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

IBM Big Data Hub

DECEMBER 20, 2023

The most common unsupervised learning method is cluster analysis, which uses clustering algorithms to categorize data points according to value similarity (as in customer segmentation or anomaly detection ). Manage a range of machine learning models with watstonx.ai And the adoption of ML technology is only accelerating.

Machine Learning 79

Machine Learning Modeling Deep Learning Predictive Modeling 79

Domino Data Lab

JULY 22, 2019

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. They’d like to do something more efficient when they’re training a lot of deep learning models.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

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

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 68

Data Science Machine Learning Big Data Interactive 68

Ontotext

FEBRUARY 26, 2024

Further, RED’s underlying model can be visually extended and customized to complex extraction and classification tasks. For every piece of processed content, RED visualizes the corresponding stock price fluctuation on a timeline, enabling users to quickly spot any immediate correlations between events and price changes.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

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. But Python is a special case: this year, more than in year’s past, its growth was buoyed by interest in ML. 3] ML and AI aren’t in any sense the same thing, either.

Data-driven 335

Data-driven Software Statistics Marketing 335

Domino Data Lab

APRIL 3, 2019

That resulted in server farms, collecting volumes of log data from customer interactions, data which was then aggregated and fed into machine learning algorithms which created data products as pre-computed results, which in turn made web apps smarter and enhanced e-commerce revenue. In short, the virtuous cycle is growing.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Occam's Razor

AUGUST 28, 2017

Over the last couple years, I’ve spent an increasing amount of time diving into the possibilities Deep Learning (DL) offers in terms of what we can do with Artificial Intelligence (AI). The first eye-opening learning for me came from the Google Research team’s post on Learning from Large-Scale Interaction.

Deep Learning 139

Deep Learning Machine Learning Marketing Strategy 139

Insight

DECEMBER 30, 2019

Take a look at this animation from Wikipedia to visualize what is happening: Figure 3?—?animation A warped wall detector: a qualitative look at kernels If you visualize your input image as a 2-D array of pixels, imagine a much smaller 2-D array called a “kernel” sweeping across it, kind of like this: Figure 4?—?Visualization

Visualization 72

Visualization Modeling Machine Learning IT 72

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

Alation

APRIL 14, 2022

Visual Profiling. Supports the ability to interact with the actual data and perform analysis on it. They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning. Parametrization. A technique to automate changes in iterative passes. Pattern Matching. Scheduling.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

bridgei2i

APRIL 13, 2020

She goes on to add that ‘Understanding vision and building visual systems are really about understanding intelligence.’ In general, the emerging global health crisis has necessitated a change in how even limited human interactions are evolving.

Insurance 52

Insurance Manufacturing Deep Learning Enterprise 52

Domino Data Lab

AUGUST 29, 2019

This article provides an excerpt “Deep Reinforcement Learning” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The article includes an overview of reinforcement learning theory with focus on the deep Q-learning. Interacting with an OpenAI Gym Environment.

Optimization 111

Optimization Modeling Deep Learning Metrics 111