Insight

MAY 14, 2020

In this post, I demonstrate how deep learning can be used to significantly improve upon earlier methods, with an emphasis on classifying short sequences as being human, viral, or bacterial. As I discovered, deep learning is a powerful tool for short sequence classification and is likely to be useful in many other applications as well.

Deep Learning 98

Deep Learning Statistics Modeling Machine Learning 98

KDnuggets

AUGUST 1, 2019

Getting trained neural networks to be deployed in applications and services can pose challenges for infrastructure managers. Challenges like multiple frameworks, underutilized infrastructure and lack of standard implementations can even cause AI projects to fail. This blog explores how to navigate these challenges.

Deep Learning 118

Deep Learning Modeling Management 118

KDnuggets

OCTOBER 10, 2019

We illustrate how to show the activation maps of various layers in a deep CNN model with just a couple of lines of code.

Deep Learning 121

Deep Learning Modeling 121

Data Science 101

SEPTEMBER 24, 2019

Is the list missing a project released in 2019? Open Source Data Science Projects. If so, please leave a comment.

Data Science 104

Data Science Deep Learning Machine Learning Visualization 104

O'Reilly on Data

FEBRUARY 4, 2019

In this post, I’ll describe some of the key areas of interest and concern highlighted by respondents from Europe, while describing how some of these topics will be covered at the upcoming Strata Data conference in London (April 29 - May 2, 2019). Machine Learning model lifecycle management. Deep Learning.

Machine Learning 279

Machine Learning Enterprise IoT Big Data 279

O'Reilly on Data

JUNE 27, 2019

Improvements in documentation, ease-of-use, and its production-ready implementation of key deep learning models, combined with speed, scalability, and accuracy has made Spark NLP a viable option for enterprises needing an NLP library. A three-part series on “Comparing production-grade NLP libraries”.

Deep Learning 188

Deep Learning Enterprise Modeling IT 188

DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. ModelOps and MLOps fall under the umbrella of DataOps,with a specific focus on the automation of data science model development and deployment workflows.

Testing 300

Testing Machine Learning Consulting Data Science 300

Corinium

JUNE 6, 2019

Beyond that, we recommend setting up the appropriate data management and engineering framework including infrastructure, harmonization, governance, toolset strategy, automation, and operating model. It is also important to have a strong test and learn culture to encourage rapid experimentation. What differentiates Fractal Analytics?

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

O'Reilly on Data

MARCH 31, 2020

Instead of writing code with hard-coded algorithms and rules that always behave in a predictable manner, ML engineers collect a large number of examples of input and output pairs and use them as training data for their models. The model is produced by code, but it isn’t code; it’s an artifact of the code and the training data.

Management 363

Management Machine Learning Experimentation Metrics 363

Smart Data Collective

MAY 2, 2019

Big data is vital for helping SEO companies identify and rectify inefficiencies in their models. There are a number of deep learning tools that evaluate social media activity. Local businesses need to rely heavily on SEO in 2019. Deep learning and other big data tools will be essential in the year is moving forward.

Big Data 112

Big Data Optimization Modeling Deep Learning 112

Dataiku

JUNE 26, 2020

In the last few years, we’ve seen a lot of breakthroughs in reinforcement learning (RL). From 2013 with the first deep learning model to successfully learn a policy directly from pixel input using reinforcement learning to the OpenAI Dexterity project in 2019, we live in an exciting moment in RL research.

Deep Learning 105

Deep Learning Modeling 105

datapine

NOVEMBER 19, 2019

While we’ve seen traces of this in 2019, it’s in 2020 that computer vision will make a significant mark in both the consumer and business world. Already in our shortlist of tech buzzwords 2019, artificial intelligence is on the front scene for next year again. Artificial Intelligence (AI). Connected Retail. Hyperautomation.

Technology 279

Technology Internet of Things IT IoT 279

Cloudera

MARCH 13, 2019

A Data Scientist : Organizations who show how they improved analytics, delivered new actionable intelligence, or designed systems for distributed deep learning and artificial intelligence to the organization’s business and customers. Stay tuned for March 19, 2019 as the winners are unveiled at the Luminaries dinner in Barcelona.

Data Architecture 69

Data Architecture Deep Learning Machine Learning Big Data 69

KDnuggets

DECEMBER 2, 2019

The latest release of MobileNets incorporates AutoML and other novel ideas in mobile deep learning.

Deep Learning 111

Deep Learning Modeling Machine Learning 111

KDnuggets

JULY 24, 2019

Recently, researchers from the Google Brain team published a paper proposing a new method called Concept Activation Vectors (CAVs) that takes a new angle to the interpretability of deep learning models.

Deep Learning 123

Deep Learning Publishing Modeling 123

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

by TAMAN NARAYAN & SEN ZHAO A data scientist is often in possession of domain knowledge which she cannot easily apply to the structure of the model. 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.

Machine Learning 111

Machine Learning Deep Learning Modeling Interactive 111

KDnuggets

NOVEMBER 13, 2019

While the revolution of deep learning now impacts our daily lives, these networks are expensive. Approaches in transfer learning promise to ease this burden by enabling the re-use of trained models -- and this hands-on tutorial will walk you through a transfer learning technique you can run on your laptop.

Deep Learning 106

Deep Learning Modeling Machine Learning 106

CIO Business Intelligence

APRIL 25, 2023

A transformer is a type of AI deep learning model that was first introduced by Google in a research paper in 2017. Five years later, transformer architecture has evolved to create powerful models such as ChatGPT. Meanwhile, however, many other labs have been developing their own generative AI models.

Experimentation 116

Experimentation Deep Learning Enterprise Modeling 116

CIO Business Intelligence

OCTOBER 4, 2023

We’ve been working on this for over a decade, including transformer-based deep learning,” says Shivananda. An example of the impact of AI can be seen from 2019 to 2022, when the company’s loss rate reduced by almost half, in part thanks to advances in algorithms and AI technology.

Digital Transformation 132

Digital Transformation Deep Learning Data Lake Risk 132

CIO Business Intelligence

JANUARY 23, 2023

As OpenAI’s exclusive cloud provider it will see additional revenue for its Azure services, as one of OpenAI’s biggest costs is providing the computing capacity to train and run its AI models. The deal, announced by OpenAI and Microsoft on Jan. Additionally, it may not always be able to understand or respond to certain inputs correctly.”

Enterprise 131

Enterprise Deep Learning Recreation/Entertainment Interactive 131

KDnuggets

NOVEMBER 18, 2019

When training a neural network in deep learning, its performance on processing new data is key. Improving the model's ability to generalize relies on preventing overfitting using these important methods.

Deep Learning 94

Deep Learning Modeling IT 94

KDnuggets

AUGUST 9, 2019

Anyone working on non-trivial deep learning models in Pytorch such as industrial researchers, Ph.D. The models we're talking about here might be taking you multiple days to train or even weeks or months. Who is this guide for? students, academics, etc.

Deep Learning 97

Deep Learning Modeling 97

Domino Data Lab

JULY 2, 2019

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. See also: Caroline Lemieux’s slides for that NeurIPS talk, and Rohan Bavishi’s video from the RISE Summer Retreat 2019. Introduction. Welcome back to our monthly burst of themespotting and conference summaries.

Metadata 105

Metadata Data Science Machine Learning Data-driven 105

KDnuggets

AUGUST 5, 2019

Generative Adversarial Networks are driving important new technologies in deep learning methods. With so much to learn, these two videos will help you jump into your exploration with GANs and the mathematics behind the modelling.

Deep Learning 93

Deep Learning Modeling Technology Machine Learning 93

CIO Business Intelligence

JUNE 7, 2022

Those numbers represent the projected growth of chatbot interactions among banking customers between 2019 to 2023 and the cost savings from 862 hours less of work by support personnel, according to research by Juniper Research. In business, when a trend is forecast to grow by more than 3000% and generate cost savings of $7.3

Unstructured Data 98

Unstructured Data Deep Learning Insurance Interactive 98

bridgei2i

MAY 14, 2019

BANGALORE, May 14, 2019. BRIDGEi2i is pleased to host Alex Smola – VP & Distinguished Scientist at AWS for an informative and hands-on learning session on Computer Vision GluconCV & D2L.ai on 18th May 2019 at the BRIDGEi2i auditorium. For more details on the meetup, please click here. About Alex Smola.

Contextual Data 63

Contextual Data Deep Learning Data Processing Consulting 63

Domino Data Lab

SEPTEMBER 9, 2019

We have configured the default Compute Environment in Domino to include all of the packages, libraries, models, and data you’ll need for this tutorial. That nlp variable is now your gateway to all things spaCy and loaded with the en_core_web_sm small model for English. deep learning on edge devices. Getting Started.

Deep Learning 110

Deep Learning Machine Learning Data Science Visualization 110

CIO Business Intelligence

APRIL 15, 2022

Derek Driggs, a machine learning researcher at the University of Cambridge, together with his colleagues, published a paper in Nature Machine Intelligence that explored the use of deep learning models for diagnosing the virus. The paper determined the technique not fit for clinical use.

Analytics 145

Analytics Machine Learning Insurance Testing 145

TDAN

JUNE 2, 2020

With multiple technologies involved, even deep learning algorithms can’t do the trick. 2019 witnessed record-breaking AI funding, and it’s mostly possible because, over the years, decision making has […]. The domain of AI and data science so far has created significant value in the technological landscape.

Data Science 52

Data Science Deep Learning Technology Business Intelligence 52

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. Of course, other BI tools such as Power BI and Qlikview also have their own advantages. From Google.

Knowledge Discovery 98

Knowledge Discovery Visualization Data mining Reporting 98

KDnuggets

OCTOBER 16, 2019

This week on KDnuggets: Beyond Word Embedding: Key Ideas in Document Embedding; The problem with metrics is a big problem for AI; Activation maps for deep learning models in a few lines of code; There is No Such Thing as a Free Lunch; 8 Paths to Getting a Machine Learning Job Interview; and much, much more.

Metrics 59

Metrics Deep Learning Machine Learning Modeling 59

Smart Data Collective

OCTOBER 14, 2019

Ludwig is a tool that allows people to build data-based deep learning models to make predictions. In September 2019, Google decided to make it’s Differential Privacy Library available as an open-source tool. Here are some open-source options to consider.

Data Science 93

Data Science Machine Learning Big Data Interactive 93

Cloudera

NOVEMBER 15, 2021

In other words, structured data has a pre-defined data model , whereas unstructured data doesn’t. . It facilitates AI because, to be useful, many AI models require large amounts of data for training. Deep Learning, a subset of AI algorithms, typically requires large amounts of human annotated data to be useful.

Unstructured Data 90

Unstructured Data Recreation/Entertainment Structured Data Reporting 90

Domino Data Lab

MARCH 3, 2019

O’Reilly Media published our analysis as free mini-books: The State of Machine Learning Adoption in the Enterprise (Aug 2018). Evolving Data Infrastructure: Tools and Best Practices for Advanced Analytics and AI (Jan 2019). AI Adoption in the Enterprise: How Companies Are Planning and Prioritizing AI Projects in Practice (Feb 2019).

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Cloudera

OCTOBER 1, 2022

It is pretty impressive just how much has changed in the enterprise machine learning and AI landscape. Thinking back to the conversations I had in late 2019, early 2020, most of the mainstream organizations I was talking to, meaning not the Facebooks and the Googles of the world, had very similar machine learning and AI journeys.

Data Governance 75

Data Governance Strategy Enterprise Machine Learning 75

CIO Business Intelligence

MAY 1, 2024

ChatGPT e le hallucination sui casi giudiziari I progressi compiuti nel 2023 dai large language models (LLM) hanno suscitato un interesse diffuso per il potenziale di trasformazione dell’IA generativa in quasi tutti i settori. “Anche quando è la tecnologia ad automatizzare la discriminazione, la responsabilità ricade sul datore di lavoro”.

Software 105

Software Deep Learning Machine Learning Modeling 105

KDnuggets

OCTOBER 14, 2019

Also: Activation maps for deep learning models in a few lines of code; The 4 Quadrants of Data Science Skills and 7 Principles for Creating a Viral Data Visualization; OpenAI Tried to Train AI Agents to Play Hide-And-Seek but Instead They Were Shocked by What They Learned; 10 Great Python Resources for Aspiring Data Scientists.

Deep Learning 51

Deep Learning Visualization Data Science Modeling 51