datapine

AUGUST 14, 2019

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

O'Reilly on Data

JANUARY 29, 2019

In 2017, we published “ How Companies Are Putting AI to Work Through Deep Learning ,” a report based on a survey we ran aiming to help leaders better understand how organizations are applying AI through deep learning. We found companies were planning to use deep learning over the next 12-18 months.

Deep Learning 208

Deep Learning Machine Learning Data Science Metadata 208

CIO Business Intelligence

JANUARY 24, 2024

It’s the culmination of a decade of work on deep learning AI. Deep learning AI: A rising workhorse Deep learning AI uses the same neural network architecture as generative AI, but can’t understand context, write poems or create drawings. You probably know that ChatGPT wasn’t built overnight.

Deep Learning 93

Deep Learning Unstructured Data Machine Learning Modeling 93

TDAN

JUNE 2, 2020

The domain of AI and data science so far has created significant value in the technological landscape. With multiple technologies involved, even deep learning algorithms can’t do the trick. However, the path to reaching success isn’t easy and quick.

Data Science 52

Data Science Deep Learning Technology Business Intelligence 52

CIO Business Intelligence

JUNE 7, 2022

More specifically: Descriptive analytics uses historical and current data from multiple sources to describe the present state, or a specified historical state, by identifying trends and patterns. In business analytics, this is the purview of business intelligence (BI). Data analytics and data science are closely related.

Data Analytics 133

Data Analytics Diagnostic Analytics Management Analytics 133

Domino Data Lab

JULY 22, 2019

Paco Nathan presented, “Data Science, Past & Future” , at Rev. At Rev’s “ Data Science, Past & Future” , Paco Nathan covered contextual insight into some common impactful themes over the decades that also provided a “lens” help data scientists, researchers, and leaders consider the future.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

O'Reilly on Data

FEBRUARY 11, 2019

Recent improvements in tools and technologies has meant that techniques like deep learning are now being used to solve common problems, including forecasting, text mining and language understanding, and personalization. AI and machine learning in the enterprise. Deep Learning. Foundational data technologies.

Big Data 209

Big Data Technology Machine Learning Deep Learning 209

CIO Business Intelligence

AUGUST 4, 2022

Interestingly, many companies do just that, creating a disconnect between data science teams and IT/DevOps when it comes to AI development. For example, many prefer to develop with deep learning frameworks such as PyTorch on a dedicated system, while others schedule their work using Slurm or Kubeflow. MLOps to the rescue.

Deep Learning 126

Deep Learning Data Science Enterprise Modeling 126

Jen Stirrup

MAY 5, 2020

Recently, I gave a Make Your Data Work Monday webinar on the complexities of the data sources for data science in Azure, and I thought it important enough to turn into an actual post. How can you differentiate the different opportunities to store your data in Azure?

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

CIO Business Intelligence

OCTOBER 13, 2023

AI researchers help develop new models and algorithms that will improve the efficiency of generative AI tools and systems, improve current AI tools, and identify opportunities for how AI can be used to improve processes or achieve business needs.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

Analytics Vidhya

OCTOBER 4, 2022

Introduction From the past two decades machine learning, Artificial intelligence and Data Science have completely revolutionized the traditional technologies.

Machine Learning 245

Machine Learning Data Science Analytics Technology 245

CIO Business Intelligence

JANUARY 25, 2024

Understand the technology For companies to maximize the business value of AI , employees must be able to communicate effectively about the technology. That doesn’t mean getting certifications in deep learning or mastering natural language processing. People need to take the enigma out of AI and make it human,” Subbaiah says.

Deep Learning 107

Deep Learning Cost-Benefit Statistics Manufacturing 107

CIO Business Intelligence

OCTOBER 4, 2023

Forward-looking disruptive technologies Although the brand has various cutting-edge technologies in its hands, one of the most relevant for the future development of the business is AI. We’ve been working on this for over a decade, including transformer-based deep learning,” says Shivananda.

Digital Transformation 128

Digital Transformation Deep Learning Data Lake Risk 128

Birst BI

NOVEMBER 20, 2018

When you hear about Data Science, Big Data, Analytics, Artificial Intelligence, Machine Learning, or Deep Learning, you may end up feeling a bit confused about what these terms mean. And most importantly, what can this do for your business? So, what do these terms really mean?

Statistics 84

Statistics Machine Learning Deep Learning Optimization 84

CIO Business Intelligence

JANUARY 26, 2024

University of California – Berkeley The University of California – Berkeley Department of Electrical Engineering and Computer Sciences focuses its foundational research in core areas of deep learning, knowledge representation, reasoning, learning, planning, decision-making, vision, robotics, speech, and NLP.

Machine Learning 104

Machine Learning Statistics Recreation/Entertainment Data Science 104

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. Data Sourcing. Deep Learning, Machine Learning, and Automation.

Predictive Analytics 122

Predictive Analytics Analytics Predictive Modeling Data mining 122

CIO Business Intelligence

AUGUST 11, 2023

Lilly Translate uses NLP and deep learning language models trained with life sciences and Lilly content to provide real-time translation of Word, Excel, PowerPoint, and text for users and systems. Licensed by MIT, SpaCy was made with high-level data science in mind and allows deep data mining.

Unstructured Data 141

Unstructured Data Modeling Machine Learning Data mining 141

CIO Business Intelligence

MAY 20, 2022

The University of California–Berkeley Department of Electrical Engineering and Computer Sciences focuses its foundational research in core areas of deep learning, knowledge representation, reasoning, learning, planning, decision-making, vision, robotics, speech, and NLP. University of California–Berkeley.

Machine Learning 145

Machine Learning Statistics Recreation/Entertainment Data Science 145

CIO Business Intelligence

APRIL 25, 2022

As a result, data scientists often spend too much time on IT operations tasks, like figuring out how to allocate computing resources, rather than actually creating and training data science models. Ready to evolve your analytics strategy or improve your data quality? Just starting out with analytics?

Machine Learning 131

Machine Learning Enterprise Deep Learning Cost-Benefit 131

CIO Business Intelligence

JUNE 1, 2022

For businesses like the McLaren Group, these two trends are at the core of the conglomerate’s digital transformation and competitive strategy, on and off the track. . Like professional basketball, industrial-scale farming, national politics, and global merchandising, auto racing has become a data science.

Manufacturing 109

Manufacturing Digital Transformation Predictive Analytics Strategy 109

IBM Big Data Hub

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. When used strategically, text-mining tools can transform raw data into real business intelligence , giving companies a competitive edge. What is text mining? How does text mining work?

Data mining 58

Data mining Machine Learning Deep Learning Marketing 58

CIO Business Intelligence

APRIL 27, 2022

Initially, BEN Group’s data science teams used cloud computing to develop and experiment with their AI models. The applications were trained to look at terabytes of unstructured data including images, text data, video and audio to identify the right influencers for a specific brand.

Modeling 52

Modeling Advertising Unstructured Data Cost-Benefit 52

CIO Business Intelligence

JUNE 2, 2022

Davis and her team are using HPC-driven data science and AI to model solutions whereby energy management systems would protect themselves with semi-automated, real-time data analysis. Ready to evolve your analytics strategy or improve your data quality? Just starting out with analytics?

Informatics 91

Informatics Modeling Testing Technology 91

FineReport

DECEMBER 19, 2019

If you want to learn more about self-service BI tools, you can take a look at this review: 5 Most Popular Business Intelligence (BI) Tools in 2019 , to understand your own needs and then choose the tool that is right for you. Pandas is a Python data science library that is constantly improving. From Google.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

CIO Business Intelligence

JANUARY 4, 2023

In the HPC community, we recognize a need for tools to support machine learning operations and data science management; these tools must be able to scale and integrate with HPC software, compute and storage environments. Ready to evolve your analytics strategy or improve your data quality?

Cost-Benefit 59

Cost-Benefit Machine Learning Modeling Uncertainty 59

Cloudera

SEPTEMBER 12, 2018

It was deeply gratifying to see so many organizations deploying the tools and techniques of data science and advanced analytics to solve difficult and important problems. I predict that next year’s competition will be even more amazing as we continue pushing the frontiers of data science forward. Societal Impact:

Machine Learning 46

Machine Learning Big Data Data Science Data Warehouse 46

Smart Data Collective

SEPTEMBER 9, 2019

Artificial intelligence is upending the financial management industry in spectacular ways. The majority of machine learning and deep learning solutions have focused on fundamental analysis of securities. Will deep learning and AI finally make technical analysis a mainstream financial management strategy?

Deep Learning 67

Deep Learning Forecasting Machine Learning Strategy 67

Domino Data Lab

APRIL 3, 2019

The top three items are essentially “the devil you know” for firms which want to invest in data science: data platform, integration, data prep. Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. Rinse, lather, repeat.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

IBM Big Data Hub

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

Machine Learning 77

Machine Learning Manufacturing Cost-Benefit Deep Learning 77

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. Scale the problem to handle complex data structures. BTW, videos for Rev2 are up: [link].

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

CIO Business Intelligence

MARCH 9, 2022

However, it also supports the quality, performance, security, and governance strengths of a data warehouse. As such, the lakehouse is emerging as the only data architecture that supports business intelligence (BI), SQL analytics, real-time data applications, data science, AI, and machine learning (ML) all in a single converged platform.

Data Lake 110

Data Lake Unstructured Data Data Warehouse Data Quality 110

CIO Business Intelligence

JUNE 15, 2022

In December 2021, the Canadian supercluster Scale AI announced that three of its four new research chairs in artificial intelligence would be located in Montréal: AI for urban mobility and logistics at HEC Montréal, data science for retail at McGill University, and data-driven supply chains at Polytechnique Montréal.

Deep Learning 142

Deep Learning Data-driven Data Science Publishing 142

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. Here are some open-source options to consider.

Data Science 69

Data Science Machine Learning Big Data Interactive 69

IBM Big Data Hub

NOVEMBER 14, 2023

Data monetization strategy: Managing data as a product Every organization has the potential to monetize their data; for many organizations, it is an untapped resource for new capabilities. But few organizations have made the strategic shift to managing “data as a product.”

Strategy 111

Strategy Cost-Benefit Data-driven Measurement 111

CIO Business Intelligence

APRIL 15, 2022

Since the COVID-19 pandemic began, numerous organizations have sought to apply machine learning (ML) algorithms to help hospitals diagnose or triage patients faster. But according to the UK’s Turing Institute, a national center for data science and AI, the predictive tools made little to no difference.

Analytics 145

Analytics Machine Learning Insurance Testing 145

Alation

APRIL 14, 2022

The vision of big data freed organizations to capture more data sources at lower levels of detail and in vastly greater volumes. For example, data science always consumes “historical” data, and there is no guarantee that the semantics of older datasets are the same, even if their names are unchanged.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

CIO Business Intelligence

MARCH 22, 2023

And even if they’re used, they may not be enough to prevent an attacker from inferring sensitive information by analyzing encrypted or masked data patterns. The new class often uses advanced techniques such as deep learning, natural language processing, and computer vision to analyze and extract insights from the data.

Machine Learning 104

Machine Learning Cost-Benefit Modeling Risk 104