Smart Data Collective

OCTOBER 1, 2020

We have previously written about the benefits of data driven marketing , but wanted to focus more on the benefits of machine learning as well. Machine learning is one of the technological advances that has played in important role in the evolution of email marketing. One of the biggest benefits is list segmentation.

Machine Learning 145

Machine Learning ROI Marketing Advertising 145

Analytics Vidhya

JULY 12, 2023

One often encounters datasets with categorical variables in data analysis and machine learning. However, many machine learning algorithms require numerical input. These variables represent qualitative attributes rather than numerical values. This is where label encoding comes into play.

Machine Learning 269

Machine Learning Analytics Data mining 269

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. This article was published as a part of the Data Science Blogathon.

Machine Learning 285

Machine Learning Data Science Publishing Analytics 285

Smart Data Collective

SEPTEMBER 8, 2021

Machine learning has made app development much easier than ever, even for people without previous coding experience. With machine learning, app development has become streamlined so much that, most people can use software to create apps without previous coding knowledge. Where Machine Learning and App Building Meets.

Machine Learning 130

Machine Learning Software Testing IT 130

Smart Data Collective

SEPTEMBER 13, 2023

Machine Learning is Crucial for Success in Digital Marketing If you have a Spotify or Netflix account, you have probably noticed a trend. When you watch or listen to something one day, the next day you will have a whole category of recommendations from the same genre as your most played or watched. Does it add value?

Machine Learning 124

Machine Learning Marketing Strategy Optimization 124

O'Reilly on Data

MAY 14, 2020

This role includes everything a traditional PM does, but also requires an operational understanding of machine learning software development, along with a realistic view of its capabilities and limitations. In our previous article, What You Need to Know About Product Management for AI , we discussed the need for an AI Product Manager.

Management 364

Management Experimentation B2B Machine Learning 364

Smart Data Collective

FEBRUARY 28, 2023

Machine learning technology has already had a huge impact on our lives in many ways. There are numerous ways that machine learning technology is changing the financial industry. However, machine learning can also help financial professionals as well. What is risk parity? How is risk parity implemented?

Machine Learning 117

Machine Learning Risk Cost-Benefit Marketing 117

Smart Data Collective

NOVEMBER 16, 2022

Machine learning technology is one of the new technologies that has drastically changed the state of video editing. Machine learning also makes it easier for video editors to create more engaging videos by utilizing unique features that were not previously possible. Keep reading to learn more.

Machine Learning 131

Machine Learning Marketing Software Reporting 131

Analytics Vidhya

APRIL 15, 2021

SUPERVISED LEARNING Before making you understand the broad category of. The post Understanding Supervised and Unsupervised Learning appeared first on Analytics Vidhya. ArticleVideo Book This article was published as a part of the Data Science Blogathon.

Data Science 367

Data Science Publishing Analytics Structured Data 367

David Menninger's Analyst Perspectives

NOVEMBER 19, 2024

 As I previously explained , although data quality and data observability are closely related and complementary, they are separate product categories. Bigeye’s anomaly detection capabilities rely on the automated generation of data quality thresholds based on machine learning (ML) models fueled by historical data.

Data Quality 130

Data Quality Dashboards Data-driven Software 130

CIO Business Intelligence

NOVEMBER 29, 2022

In a bid to help enterprises offer better customer service and experience , Amazon Web Services (AWS) on Tuesday, at its annual re:Invent conference, said that it was adding new machine learning capabilities to its cloud-based contact center service, Amazon Connect. Cloud Computing, Enterprise Applications, Machine Learning

Machine Learning 111

Machine Learning Forecasting Recreation/Entertainment Metrics 111

Analytics Vidhya

NOVEMBER 29, 2021

Introduction Consider the following scenario: you are a product manager who wants to categorize customer feedback into two categories: favorable and unfavorable. This article was published as a part of the Data Science Blogathon. Or As a loan manager, do you want to know which loan applications are safe to lend to and which ones […].

Data Science 342

Data Science Publishing Management Analytics 342

Rocket-Powered Data Science

JULY 6, 2021

In this post, we will examine ways that your organization can separate useful content into separate categories that amplify your own staff’s performance. My favorite approach to TAM creation and to modern data management in general is AI and machine learning (ML). Before we start, I have a few questions for you.

Strategy 267

Strategy Machine Learning Metadata Knowledge Discovery 267

O'Reilly on Data

JUNE 19, 2019

A look at the landscape of tools for building and deploying robust, production-ready machine learning models. Our surveys over the past couple of years have shown growing interest in machine learning (ML) among organizations from diverse industries. Why aren’t traditional software tools sufficient?

Modeling 256

Modeling Machine Learning Testing Metrics 256

David Menninger's Analyst Perspectives

OCTOBER 6, 2023

Drawing on our Benchmark Research, we apply a structured methodology built on evaluation categories that reflect the real-world criteria incorporated in a request for proposal to Analytics and Data vendors supporting the spectrum of Augmented Analytics.

Analytics 285

Analytics ROI Marketing Management 285

Analytics Vidhya

OCTOBER 2, 2019

Overview Here are eight ambitious data science projects to add to your data science portfolio We have divided these projects into three categories – The post Add Shine to your Data Science Resume with these 8 Ambitious Projects on GitHub appeared first on Analytics Vidhya.

Data Science 307

Data Science Analytics Machine Learning Big Data 307

O'Reilly on Data

SEPTEMBER 15, 2021

It isn’t surprising that employees see training as a route to promotion—especially as companies that want to hire in fields like data science, machine learning, and AI contend with a shortage of qualified employees. Average salary by tools for statistics or machine learning. Salaries by Tool and Platform.

Machine Learning 363

Machine Learning Statistics Reporting Consulting 363

DataKitchen

APRIL 13, 2021

Because it is such a new category, both overly narrow and overly broad definitions of DataOps abound. 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. . Process Analytics.

Testing 304

Testing Machine Learning Consulting Data Science 304

Rocket-Powered Data Science

MARCH 10, 2020

The book Graph Algorithms: Practical Examples in Apache Spark and Neo4j is aimed at broadening our knowledge and capabilities around these types of graph analyses, including algorithms, concepts, and practical machine learning applications of the algorithms. It’s all here. Your team will become graph heroes.

Metadata 250

Metadata Machine Learning Prescriptive Analytics ROI 250

O'Reilly on Data

JUNE 18, 2019

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI In this post, we shed some light on various efforts toward generating data for machine learning (ML) models. Machine learning applications rely on three main components: models, data, and compute.

Machine Learning 279

Machine Learning Data Quality Statistics Modeling 279

AWS Big Data

NOVEMBER 8, 2024

You can use Amazon Redshift to analyze structured and semi-structured data and seamlessly query data lakes and operational databases, using AWS designed hardware and automated machine learning (ML)-based tuning to deliver top-tier price performance at scale. category"; Create a materialized view using the external schema.

Data Lake 105

Data Lake Data Warehouse Optimization Testing 105

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

On the other hand, sophisticated machine learning models are flexible in their form but not easy to control. Introduction Machine learning models often behave unpredictably, as data scientists would be the first to tell you. A more general approach is to learn a Generalized Additive Model (GAM).

Machine Learning 111

Machine Learning Deep Learning Modeling Interactive 111

IBM Big Data Hub

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. What is machine learning?

Machine Learning 73

Machine Learning Modeling Deep Learning Predictive Modeling 73

Rocket-Powered Data Science

FEBRUARY 15, 2023

A business-disruptive ChatGPT implementation definitely fits into this category: focus first on the MVP or MLP. Most of these rules focus on the data, since data is ultimately the fuel, the input, the objective evidence, and the source of informative signals that are fed into all data science, analytics, machine learning, and AI models.

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

O'Reilly on Data

OCTOBER 19, 2021

Much has been written about struggles of deploying machine learning projects to production. The new category is often called MLOps. This approach has worked well for software development, so it is reasonable to assume that it could address struggles related to deploying machine learning in production too.

IT 364

IT Testing Experimentation Software 364

Analytics Vidhya

AUGUST 13, 2022

The first task you do with each ticket is to classify it into one of the categories you […]. Introduction Suppose you are working in an IT firm as a support desk specialist and receive hundreds of support tickets you have to handle daily. The post Step-by-step Explanation of Text Classification appeared first on Analytics Vidhya.

Data Science 270

Data Science Publishing Analytics IT 270

Rocket-Powered Data Science

JULY 19, 2023

The criticality of these synergies becomes obvious when we recognize analytics as the products (the outputs and deliverables) of the data science and machine learning activities that are applied to enterprise data (the inputs).

Analytics 198

Analytics Data-driven Machine Learning Data Science 198

O'Reilly on Data

AUGUST 8, 2023

The number of searches for Machine Learning itself held steady, though it arguably declined slightly when ChatGPT appeared. Removing ChatGPT and Machine Learning from the previous graph makes it easier to see trends in the other popular search terms: It’s mostly “up and to the right.”

Machine Learning 246

Machine Learning Modeling Software IT 246

CIO Business Intelligence

SEPTEMBER 26, 2023

The new platform would alleviate this dilemma by using machine learning (ML) algorithms, along with source data accessed by SAP’s Data Warehouse Cloud. This year, the company was honored as a winner in the “Cutting Edge Genius” category at the SAP Innovation Awards.

Machine Learning 105

Machine Learning Forecasting Measurement Data Warehouse 105

O'Reilly on Data

SEPTEMBER 15, 2020

Outputs from trained AI models include numbers (continuous or discrete), categories or classes (e.g., In most cases, AI solutions are built to map a set of inputs to one or more outputs, where the outputs fall into a small group of possibilities. spam or not-spam), probabilities, groups/segments, or a sequence (e.g., Conclusion.

Advertising 362

Advertising Cost-Benefit ROI Machine Learning 362

Octopai

JULY 17, 2022

Automated data mapping tools come in several varieties: Data mapping software that provides a drag-and-drop interface with reusable parts, enabling data engineers or citizen integrators to speed up their process of matching fields and coding transformations Automated tools that independently suggest data mapping using machine learning techniques, leaving (..)

Machine Learning 98

Machine Learning Visualization Enterprise Software 98

CIO Business Intelligence

JANUARY 9, 2025

Before LLMs and diffusion models, organizations had to invest a significant amount of time, effort, and resources into developing custom machine-learning models to solve difficult problems. In many cases, this eliminates the need for specialized teams, extensive data labeling, and complex machine-learning pipelines.

Software 128

Software Enterprise Key Performance Indicator Machine Learning 128

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.”. Almost 33% of respondents claim that machine learning can lead to improved customer experience.

Predictive Analytics 145

Predictive Analytics Technology Analytics Machine Learning 145

David Menninger's Analyst Perspectives

MAY 15, 2025

Decades of refinement and focused development to support specific industriesand even specialized categories within these industrieshave increased their utility while decreasing the total cost of ownership, especially in implementation expense and maintenance. Cloud-based systems, in particular, are far easier to maintain.

Enterprise 130

Enterprise Management Finance Cost-Benefit 130

Rocket-Powered Data Science

DECEMBER 15, 2018

This wisdom applies not only to life but to machine learning also. Specifically, the availability and application of labeled data (things past) for the labeling of previously unseen data (things future) is fundamental to supervised machine learning. A related problem also arises in unsupervised machine learning.

Machine Learning 171

Machine Learning Optimization Metrics Deep Learning 171

Cloudera

JANUARY 7, 2021

And in the world of e-commerce, assigning product descriptions to the most fitting product category ensures quality control. . However, collecting annotations for your use case is typically one of the most costly parts of the machine learning life cycle. Another fact of real-world use cases is the uneven distribution of data.

Machine Learning 107

Machine Learning Deep Learning IT 107

AWS Big Data

NOVEMBER 7, 2024

Xiao Qin is a senior applied scientist with the Learned Systems Group (LSG) at Amazon Web Services (AWS). He studies and applies machine learning techniques to solve data management problems. This additional information can be valuable for Amazon Q to better understand the problems and make improvements.

Metadata 105

Metadata Sales Data Warehouse Optimization 105