IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? What is machine learning?

Machine Learning 60

Machine Learning Data Science Statistics Deep Learning 60

Analytics Vidhya

AUGUST 26, 2021

This article was published as a part of the Data Science Blogathon “You can have data without information but you cannot have information without data” – Daniel Keys Moran Introduction If you are here then you might be already interested in Machine Learning or Deep Learning so I need not explain what it is?

Modeling 288

Modeling Deep Learning Machine Learning Data Science 288

Analytics Vidhya

AUGUST 26, 2021

This article was published as a part of the Data Science Blogathon The intersection of medicine and data science has always been relevant; perhaps the most obvious example is the implementation of neural networks in deep learning. Nanotechnology, stem cells, […].

Deep Learning 284

Deep Learning Machine Learning Data Science Publishing 284

Smart Data Collective

JUNE 10, 2022

The average data scientist earns over $108,000 a year. The interdisciplinary field of data science involves using processes, algorithms, and systems to extract knowledge and insights from both structured and unstructured data and then applying the knowledge gained from that data across a wide range of applications.

Data Science 119

Data Science Machine Learning Statistics Business Intelligence 119

IBM Big Data Hub

DECEMBER 5, 2023

Generative AI excels at handling diverse data sources such as emails, images, videos, audio files and social media content. This unstructured data forms the backbone for creating models and the ongoing training of generative AI, so it can stay effective over time.

Unstructured Data 95

Unstructured Data Cost-Benefit Experimentation Machine Learning 95

CIO Business Intelligence

AUGUST 11, 2023

How natural language processing works NLP leverages machine learning (ML) algorithms trained on unstructured data, typically text, to analyze how elements of human language are structured together to impart meaning.

Unstructured Data 142

Unstructured Data Modeling Machine Learning Data mining 142

Smart Data Collective

AUGUST 28, 2021

Usually, business or data analysts need to extract insights for reporting purposes, so data warehouses are more suitable for them. On the other hand, a data scientist may require access to unstructured data to detect patterns or build a deep learning model, which means that a data lake is a perfect fit for them.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Structured Data 140

CIO Business Intelligence

JUNE 7, 2022

But only in recent years, with the growth of the web, cloud computing, hyperscale data centers, machine learning, neural networks, deep learning, and powerful servers with blazing fast processors, has it been possible for NLP algorithms to thrive in business environments. NLP will account for $35.1

Unstructured Data 98

Unstructured Data Deep Learning Insurance Interactive 98

IBM Big Data Hub

JULY 6, 2023

To keep up with the pace of consumer expectations, companies are relying more heavily on machine learning algorithms to make things easier. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other? Machine learning is a subset of AI.

Deep Learning 62

Deep Learning Machine Learning Unstructured Data Modeling 62

Analytics Vidhya

SEPTEMBER 7, 2020

Introduction Overfitting or high variance in machine learning models occurs when the accuracy of your training dataset, the dataset used to “teach” the model, The post How to Treat Overfitting in Convolutional Neural Networks appeared first on Analytics Vidhya.

Machine Learning 288

Machine Learning Modeling Analytics Unstructured Data 288

Analytics Vidhya

MAY 27, 2020

Introduction Every once in a while, a machine learning framework or library changes the landscape of the field. Today, Facebook open sourced one such. The post Facebook AI Launches DEtection TRansformer (DETR) – A Transformer based Object Detection Approach! appeared first on Analytics Vidhya.

Machine Learning 307

Machine Learning Analytics Unstructured Data Deep Learning 307

IBM Big Data Hub

FEBRUARY 14, 2024

Using machine learning (ML), AI can understand what customers are saying as well as their tone—and can direct them to customer service agents when needed. These systems can evaluate vast amounts of data to uncover trends and patterns, and to make decisions.

Cost-Benefit 89

Cost-Benefit Insurance Unstructured Data Machine Learning 89

datapine

AUGUST 14, 2019

Data science tools are used for drilling down into complex data by extracting, processing, and analyzing structured or unstructured data to effectively generate useful information while combining computer science, statistics, predictive analytics, and deep learning. Source: RStudio. Source: mathworks.com.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

IBM Big Data Hub

AUGUST 28, 2023

Text mining —also called text data mining—is an advanced discipline within data science that uses natural language processing (NLP) , artificial intelligence (AI) and machine learning models, and data mining techniques to derive pertinent qualitative information from unstructured text data.

Data mining 58

Data mining Machine Learning Deep Learning Marketing 58

bridgei2i

OCTOBER 7, 2020

The automated process can then be used to parse data sources like structured and unstructured data sources such as – IoT data, claims data, physical proofs, social data, life health data and in a variety of formats such as textual, visual, sensor-based and electronic etc. The way ahead for insurers.

Insurance 52

Insurance Sales Strategy Digital Transformation 52

Analytics Vidhya

APRIL 8, 2023

Introduction More businesses are moving online these days, and consumers are ordering online instead of traveling to the store to buy. Zomato and Swiggy are popular online platforms for ordering food products. Other examples are Uber Eats, Food Panda, and Deliveroo, which also have similar services. They provide food delivery options.

Analytics 319

Analytics Unstructured Data Deep Learning Machine Learning 319

Domino Data Lab

AUGUST 9, 2021

Before selecting a tool, you should first know your end goal – machine learning or deep learning. Machine learning identifies patterns in data using algorithms that are primarily based on traditional methods of statistical learning. It’s most helpful in analyzing structured data.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

Analytics Vidhya

OCTOBER 8, 2020

This article was published as a part of the Data Science Blogathon. Introduction Fastai is a popular open-source library used for learning and practicing. The post Develop and Deploy an Image Classifier App Using Fastai appeared first on Analytics Vidhya.

Data Science 365

Data Science Publishing Analytics Unstructured Data 365

Analytics Vidhya

OCTOBER 7, 2020

This article was published as a part of the Data Science Blogathon. Introduction The article covers the use of Generative Adversarial Networks (GAN), an. The post Boost Model Accuracy of Imbalanced COVID-19 Mortality Prediction Using GAN-based Oversampling Technique appeared first on Analytics Vidhya.

Modeling 296

Modeling Data Science Publishing Analytics 296

DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. .

Testing 307

Testing Machine Learning Consulting Data Quality 307

IBM Big Data Hub

JANUARY 10, 2024

AI operates on three fundamental components: data, algorithms and computing power. Data: AI systems learn and make decisions based on data, and they require large quantities of data to train effectively, especially in the case of machine learning (ML) models.

Unstructured Data 84

Unstructured Data Deep Learning Cost-Benefit Modeling 84

Sisense

MAY 26, 2020

In this post, we’ll discuss these challenges in detail and include some tips and tricks to help you handle text data more easily. Unstructured data and Big Data. Most common challenges we face in NLP are around unstructured data and Big Data. is “big” and highly unstructured.

Unstructured Data 98

Unstructured Data Big Data Testing Machine Learning 98

CIO Business Intelligence

MARCH 9, 2022

As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

Domino Data Lab

AUGUST 10, 2021

Models are the central output of data science, and they have tremendous power to transform companies, industries, and society. At the center of every machine learning or artificial intelligence application is the ML/AI model that is built with data, algorithms and code. It’s used for developing deep learning models.

Modeling 64

Modeling IT Risk Management Deep Learning 64

Ontotext

MAY 22, 2023

This is the case with the so-called intelligent data processing (IDP), which uses a previous generation of machine learning. Luckily, the text analysis that Ontotext does is focused on tasks that require complex domain knowledge and linking of documents to reference data or master data.

Management 59

Management Unstructured Data Metadata Cost-Benefit 59

IBM Big Data Hub

AUGUST 1, 2023

It’s the underlying engine that gives generative models the enhanced reasoning and deep learning capabilities that traditional machine learning models lack. That’s where the foundation model enters the picture. They can also quickly and accurately translate marketing collateral into multiple languages.

Modeling 61

Modeling Cost-Benefit Data Lake Machine Learning 61

Domino Data Lab

JULY 2, 2019

Doesn’t this seem like a worthy goal for machine learning—to make the machines learn to work more effectively? Scale the problem to handle complex data structures. Part of the back-end processing needs deep learning (graph embedding) while other parts make use of reinforcement learning.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Ontotext

FEBRUARY 26, 2024

Using machine learning, RED indicates the impact of events on stock prices. It compares actual price changes to expected changes based on historical data. This semantic model serves as a blueprint or framework against which raw data is analyzed and organized. Let’s have a quick look under the bonnet.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

DataRobot

NOVEMBER 9, 2021

When we convert the single channel audio signal time series into an energy spectrogram, it allows us to run state of the art deep learning architectures on the image. . Spectrograms are not the only transformations available to convert signal data to images. Image courtesy towardsAI.

Visualization 52

Visualization Unstructured Data Statistics Metrics 52

datapine

NOVEMBER 19, 2019

An important part of artificial intelligence comprises machine learning, and more specifically deep learning – that trend promises more powerful and fast machine learning. An exemplary application of this trend would be Artificial Neural Networks (ANN) – the predictive analytics method of analyzing data.

Technology 279

Technology Internet of Things IT IoT 279

IBM Big Data Hub

MAY 17, 2023

The services are activated through access management for data collection, analysis and event monitoring in existing drones which are managed by clients and businesses. The flexibility of DaaS in offering a multiplicity of data collection services for different industry use cases makes it unique.

Data Collection 84

Data Collection Visualization Data-driven Unstructured Data 84

CIO Business Intelligence

JANUARY 20, 2023

Modern compute infrastructures are designed to enhance business agility and time to market by supporting workloads for databases and analytics, AI and machine learning (ML), high performance computing (HPC) and more. Ready to evolve your analytics strategy or improve your data quality? Just starting out with analytics?

Analytics 137

Analytics Key Performance Indicator Unstructured Data IoT 137

Smart Data Collective

MARCH 16, 2020

Deep learning is likely to play an essential role in keeping costs in check. Deep Learning is Necessary to Create a Sustainable Medicare for All System. He should elaborate more on the benefits of big data and deep learning. They argued that machine learning could make healthcare much more efficient.

Deep Learning 80

Deep Learning Unstructured Data Cost-Benefit Big Data 80