CIO Business Intelligence

SEPTEMBER 29, 2023

Analyzing the hiring behaviors of companies on its platform, freelance work marketplace Upwork has AI to be the fastest growing category for 2023, noting that posts for generative AI jobs increased more than 1000% in Q2 2023 compared to the end of 2022, and that related searches for AI saw a more than 1500% increase during the same time.

Deep Learning 142

Deep Learning Machine Learning Modeling Consulting 142

IBM Big Data Hub

MARCH 27, 2024

Within USEEIO, goods and services are categorized into 66 spend categories, referred to as commodity classes, based on their common environmental characteristics. This involves mapping the 15.909 sectors found across the Eora26 categories and more detailed national sector classifications to the USEEIO 66 spend categories.

Experimentation 80

Experimentation Modeling Deep Learning Data-driven 80

Ontotext

DECEMBER 15, 2023

The official (first) repo is tensorflow/tensor2tensor that has topics: machine-learning reinforcement-learning deep-learning machine-translation tpu. By exploring the first topic machine-learning , we find 117k Github repos. Wikipedia categories are used to classify articles, and to form a hierarchy.

Machine Learning 69

Machine Learning Interactive Deep Learning Statistics 69

Data Science 101

DECEMBER 27, 2019

AWS Deep Learning Containers now support Tensorflow 2.0 AWS Deep Learning Containers are docker images which are preconfigured for deep learning tasks. It walks through classifying Yahoo Answers into different categories. Here are the few bits of information I could find. Signup for the Newsletter.

Data Science 86

Data Science Deep Learning Data-driven IT 86

Analytics Vidhya

FEBRUARY 22, 2022

Introduction Every supervised machine learning technique basically solves either classification or regression problems. Classification is a kind of technique where we classify the outcome into distinct categories whose range is usually finite. Whereas a regression technique involves predicting a real number whose range is […].

Machine Learning 246

Machine Learning Data Science Publishing Analytics 246

Laminar Security

DECEMBER 13, 2023

Machine learning algorithms can be trained to recognize patterns in the data and classify data accordingly. For example, an AI system could be trained to classify emails into categories like “sensitive” or “restricted” based on patterns it has learned from a training dataset.

Data-driven 119

Data-driven Machine Learning Risk Deep Learning 119

MLWhiz

DECEMBER 16, 2018

With the problem of Image Classification is more or less solved by Deep learning, Text Classification is the next new developing theme in deep learning. How could you use that? To find sentiment of a review.

Deep Learning 85

Deep Learning 85

Cloudera

JANUARY 7, 2021

And in the world of e-commerce, assigning product descriptions to the most fitting product category ensures quality control. . Very few real-world use cases have categories that are eternally set in stone. The reality is that new classes, topics, and categories will likely emerge over time as business needs evolve.

Machine Learning 105

Machine Learning Deep Learning IT 105

CIO Business Intelligence

JUNE 2, 2022

The report, based on survey responses from tech decision makers in banks and their technology vendors, categorizes 30 different technologies into three main categories: “hot,” “on-the-radar,” and “hype.”. RPA, blockchain are on the radar for banks.

Predictive Analytics 145

Predictive Analytics Technology Analytics Machine Learning 145

CIO Business Intelligence

MAY 28, 2022

It is not always the newest technologies that pay the best. Some of the fastest-rising pay premiums during the quarter were for knowledge of the venerable DB2 and Apache Sqoop, a command-line interface for loading Hadoop databases that ceased development last year.

IT 121

IT Prescriptive Analytics Deep Learning Reporting 121

Smart Data Collective

JUNE 4, 2021

Whereas in machine learning, the algorithm understands the data and creates the logic. Learning the various categories of machine learning, associated algorithms, and their performance parameters is the first step of machine learning. Machine learning is broadly classified into three types – Supervised.

Data Science 104

Data Science Statistics Deep Learning Machine Learning 104

CIO Business Intelligence

MAY 26, 2022

It is not always the newest technologies that pay the best. Some of the fastest-rising pay premiums during the quarter were for knowledge of the venerable DB2 and Apache Sqoop, a command-line interface for loading Hadoop databases that ceased development last year.

IT 97

IT Prescriptive Analytics Deep Learning Reporting 97

CIO Business Intelligence

OCTOBER 4, 2023

This volatility can make it hard for IT workers to decide where to focus their career development efforts, but there are at least some areas of stability in the market: despite all other changes in pay premiums, workers with AI skills and security certifications continued to reap rich rewards.

Prescriptive Analytics 131

Prescriptive Analytics IT Machine Learning Risk 131

Cloudera

AUGUST 20, 2020

The imperative to deliver meaningful change and value through innovation is why the Data for Enterprise AI category at the Data Impact Awards has never been more of the moment than it is today. UOB used deep learning to improve detection of procurement fraud, thereby fighting financial crime.

Enterprise 121

Enterprise Experimentation Uncertainty Deep Learning 121

DataRobot

APRIL 6, 2020

If you’re a regular reader of the DataRobot blog, you likely fall into one of two categories.

Deep Learning 69

Deep Learning Forecasting Data Science Interactive 69

Cloudera

OCTOBER 27, 2020

Our goal is to take the incredible data science and machine learning research developments we see emerging from academia and large industrial labs, and bridge the gap to products and processes that are useful to practitioners working across industries. Evolving Research At Cloudera Fast Forward. Structural Time Series.

Deep Learning 59

Deep Learning Machine Learning Forecasting Uncertainty 59

Smart Data Collective

MARCH 16, 2022

In other cases, advanced AI applications use a deep-learning approach to sift through big data to predict the prices of stocks in the near future. However, deep-learning approaches are comprehensive in theory. For instance, real-time car purchases can help predict the price of Rolls Royce shares in the near future.

Big Data 104

Big Data Deep Learning Finance Data-driven 104

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

For categorical features, unique categories are assigned their own knots and then we learn a “PLF” (really, a 1-d embedding since every value is exactly at a knot). This formulation allows the user to specify any monotonic orderings they want between the categories, or even a total ordering (as with, say, a Likert-scale).

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

Data Science 101

MAY 20, 2019

Evaluation of Linear Regression Evaluation of Classification Positive/negative skew Poisson regression Fisher’s exact test Pearson PCA Deep learning – high-level, what is is for Neural Networks (RNN vs CNN vs DCN vs GAN). There were a number of questions from this category. Azure ML Studio. Azure Products.

Data Science 111

Data Science Machine Learning Deep Learning Testing 111

IBM Big Data Hub

JULY 6, 2023

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?

Deep Learning 61

Deep Learning Machine Learning Unstructured Data Modeling 61

CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. Models can be designed, for instance, to discover relationships between various behavior factors.

Predictive Analytics 144

Predictive Analytics Analytics Predictive Modeling Forecasting 144

Smart Data Collective

AUGUST 26, 2021

Deep learning technology is changing the future of small businesses around the world. A growing number of small businesses are using deep learning technology to address some of their most pressing challenges. New advances in deep learning are integrated into various accounting algorithms.

Deep Learning 96

Deep Learning Finance Cost-Benefit Advertising 96

Smart Data Collective

SEPTEMBER 23, 2020

Type of Data: structured and unstructured from different sources of data Purpose: Cost-efficient big data storage Users: Engineers and scientists Tasks: storing data as well as big data analytics, such as real-time analytics and deep learning Sizes: Store data which might be utilized. Data Warehouse.

Data Lake 105

Data Lake Data Warehouse Unstructured Data Big Data 105

Domino Data Lab

MARCH 16, 2021

Here we see the top 5 predicted categories for an image using a technique called Class Activation Mapping explained in this paper: [link]. DeepLIFT was recently proposed as a recursive prediction explanation method for deep learning [8, 7]. Each filter must encode a distinct object part that is exclusive to a single category.

Modeling 122

Modeling Deep Learning Testing Optimization 122

Domino Data Lab

JULY 15, 2021

Key categories of tools and a few examples include: Data Sources. Languages are typically broken into two categories, commercial and open source. Originally created for software development, Python is used in a variety of contexts, including deep learning research and model deployment. They range from flat files (e.g.

Data Science 145

Data Science Visualization Modeling Enterprise 145

Occam's Razor

MARCH 30, 2017

People tend to use these phrases almost interchangeably: Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning. Deep Learning is a specific ML technique. Most Deep Learning methods involve artificial neural networks, modeling how our bran works.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

Rocket-Powered Data Science

DECEMBER 16, 2018

It is focused on learning the right tasks to perform and on tuning the modeling hyper-parameters. Workshop on Meta-Learning (MetaLearn 2018). Finally, in addition to the awesome 750-page book “ Encyclopedia of Distances “, please check out some of these top-selling books on Data Science, AI, and Machine Learning :

Machine Learning 203

Machine Learning Metrics Optimization Data Science 203

CIO Business Intelligence

APRIL 27, 2022

Organizations can view the platforms agenda through two basic categories depending on how “elevated” the platform is in creating value. Cloud-enabled architectures are the de facto way forward due to their inherent ability to scale dynamically.

Strategy 141

Strategy Data-driven Internet of Things Measurement 141

Smart Data Collective

APRIL 24, 2020

The categories, the tags, patterns, and much more could all be recognized by deep learning algorithms, which is part of the reason why data ingestion is so effective. A good perk to point out about data lakes is that they can use powerful algorithms to help your analysts comprehend the gathered data.

Data Lake 99

Data Lake Data Collection Deep Learning Management 99

Insight

MARCH 25, 2020

In this blog, I will share how I built Pair , a scalable web application that takes in a product image, analyzes its design features using convolutional neural network, and recommends products in other categories with similar style elements. In this project, I was curious to see if deep learning approaches?—?specifically

Deep Learning 53

Deep Learning Metrics Data Processing Interactive 53

Insight

OCTOBER 25, 2019

Problem Statement For this project, my client specified a public dataset ( T-LESS ) of 30 industry-relevant objects and categorized them into seven distinct categories. Among these categories, one consists of only two objects (objects 27 and 29). Meta-Learning v.s. One being the 3-D nature of our images.

Snapshot 57

Snapshot Testing Deep Learning Visualization 57

Ontotext

MAY 22, 2023

When sales performance is analyzed and correlated with marketing data, for instance, it is critical to make sure that across the board there is good alignment regarding the categories of products, the regions, the suppliers and the relationships between them. We use other deep learning techniques for such tasks.

Management 59

Management Unstructured Data Metadata Cost-Benefit 59

O'Reilly on Data

APRIL 19, 2021

Unfortunately, we don’t know which industries are represented by that category—but it shows that the spread of AI has indeed become broad! First, 82% of the respondents are using supervised learning, and 67% are using deep learning. 58% claimed to be using unsupervised learning. Industries using AI. Techniques.

Enterprise 356

Enterprise Modeling Risk Manufacturing 356

DataKitchen

APRIL 13, 2021

Because it is such a new category, both overly narrow and overly broad definitions of DataOps abound. Metis Machine — Enterprise-scale Machine Learning and Deep Learning deployment and automation platform for rapid deployment of models into existing infrastructure and applications.

Testing 307

Testing Machine Learning Consulting Data Quality 307

IBM Big Data Hub

OCTOBER 16, 2023

Filtering email ML algorithms in Google’s Gmail automate filtering customers’ email into Primary, Social and Promotions categories while also detecting and rerouting spam to a spam folder. Reinforcement learning uses ML to train models to identify and respond to cyberattacks and detect intrusions.

Machine Learning 51

Machine Learning Marketing Forecasting Modeling 51

IBM Big Data Hub

AUGUST 28, 2023

Text classification: Useful for tasks like sentiment classification, spam filtering and topic classification, text classification involves categorizing documents into predefined classes or categories. And with advanced software like IBM Watson Assistant , social media data is more powerful than ever.

Data mining 57

Data mining Machine Learning Deep Learning Marketing 57

Business Over Broadway

DECEMBER 20, 2018

Looking ahead to 2018, data professionals are most interested in learning deep learning (41%). A recent survey, however, revealed that a limited number of data professionals possess competency in advanced machine learning skills. Also, data professionals reported experiencing around three challenges in the previous year.

Machine Learning 74

Machine Learning Data Science Deep Learning Predictive Analytics 74