Rocket-Powered Data Science

MARCH 20, 2023

We live in a data-rich, insights-rich, and content-rich world. Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. Source: [link] I will finish with three quotes.

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Unstructured Data 325

Rocket-Powered Data Science

JUNE 17, 2022

Here is a list of my top moments, learnings, and musings from this year’s Splunk.conf : Observability for Unified Security with AI (Artificial Intelligence) and Machine Learning on the Splunk platform empowers enterprises to operationalize data for use-case-specific functionality across shared datasets.

Machine Learning 238

Machine Learning Recreation/Entertainment Risk Business Objectives 238

Rocket-Powered Data Science

MARCH 19, 2021

The determination of winners and losers in the data analytics space is a much more dynamic proposition than it ever has been. One CIO said it this way , “If CIOs invested in machine learning three years ago, they would have wasted their money. A lot has changed in those five years, and so has the data landscape.

Internet of Things 259

Internet of Things Analytics IoT Prescriptive Analytics 259

O'Reilly on Data

DECEMBER 10, 2019

Roughly a year ago, we wrote “ What machine learning means for software development.” In that article, we talked about Andrej Karpathy’s concept of Software 2.0. In short, we can use machine learning to automate software development itself. Instead, we can program by example.

Software 259

Software Machine Learning Risk Data-driven 259

Rocket-Powered Data Science

JULY 6, 2021

I provide below my perspective on what was interesting, innovative, and influential in my watch list of the Top 10 data innovation trends during 2020. 1) Automated Narrative Text Generation tools became incredibly good in 2020, being able to create scary good “deep fake” articles.

Data-driven 279

Data-driven Machine Learning IoT Deep Learning 279

Rocket-Powered Data Science

JULY 21, 2023

” Model-Assisted Threat Hunts , also known as Splunk M-ATH , is Splunk’s brand name for machine learning-assisted threat hunting and mitigation. search for deviations from normal behaviors through EDA: Exploratory Data Analysis), and (3) M-ATH (i.e., faster alerting with fewer false positives and false negatives).

Machine Learning 190

Machine Learning Metrics Reporting Internet of Things 190

O'Reilly on Data

MAY 14, 2020

In our previous article, What You Need to Know About Product Management for AI , we discussed the need for an AI Product Manager. 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.

Management 363

Management Experimentation B2B Machine Learning 363

Rocket-Powered Data Science

MAY 21, 2024

To see this, look no further than Pure Storage , whose core mission is to “ empower innovators by simplifying how people consume and interact with data.” See additional references and resources at the end of this article. At the NVIDIA GTC 2024 conference, Pure Storage announced so much more!

Cost-Benefit 239

Cost-Benefit Unstructured Data Enterprise Technology 239

Smart Data Collective

JUNE 8, 2023

We have talked extensively about the many industries that have been impacted by big data. many of our articles have centered around the role that data analytics and artificial intelligence has played in the financial sector. However, many other industries have also been affected by advances in big data technology.

Data Analytics 82

Data Analytics Analytics Data Collection Statistics 82

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

O'Reilly on Data

JUNE 18, 2019

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI AI starts with ‘good’ data” is a statement that receives wide agreement from data scientists, analysts, and business owners. See this article on data integration status for details.

Machine Learning 255

Machine Learning Data Quality Statistics Modeling 255

TDAN

AUGUST 17, 2021

If you are planning on using predictive algorithms, such as machine learning or data mining, in your business, then you should be aware that the amount of data collected can grow exponentially over time.

Predictive Modeling 115

Predictive Modeling Modeling Data mining Big Data 115

CIO Business Intelligence

MAY 29, 2024

Document processing, querying data, and making recommendations are just a few business cases where AI can streamline operations, enhance decision-making, and drive competitive advantage. This article will unpack what technical foundations are needed to get started using AI and how trained AI is a competitive differentiator.

Sales 58

Sales Modeling Machine Learning Measurement 58

Rocket-Powered Data Science

JULY 7, 2019

AGI (Artificial General Intelligence): AI (Artificial Intelligence): Application of Machine Learning algorithms to robotics and machines (including bots), focused on taking actions based on sensory inputs (data). Examples: (1-3) All those applications shown in the definition of Machine Learning. (4)

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

Smart Data Collective

JULY 9, 2023

In the ever-evolving and increasingly competitive global e-commerce sector, businesses that strive to achieve and maintain high conversion rates face the pressing, yet necessary, task of harnessing the potential of accessible data. Analyzing these metrics will shed light on any barriers, which helps you reach your sales goals.

Optimization 74

Optimization Data Analytics Analytics Data-driven 74

Rocket-Powered Data Science

AUGUST 1, 2018

In the early days of the big data era (at the peak of the big data hype), we would often hear about the 3 V’s of big data (Volume, Variety, and Velocity). ” A series of articles that drive home the all-important value of data is being published on the DataMakesPossible.com site.

Big Data 105

Big Data Machine Learning Data-driven Data Science 105

Smart Data Collective

DECEMBER 17, 2021

The process of Marketing Analytics consists of data collection, data analysis, and action plan development. Understanding your marketing data to make more informed and successful marketing strategy decisions is a systematic process. Types of Data Used in Marketing Analytics. Source: [link].

Marketing Analytics 93

Marketing Analytics Marketing Data-driven Analytics 93

O'Reilly on Data

JULY 28, 2020

In this article, we turn our attention to the process itself: how do you bring a product to market? It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Product managers for AI must satisfy these same responsibilities, tuned for the AI lifecycle.

Marketing 361

Marketing Experimentation Metrics Testing 361

CIO Business Intelligence

JANUARY 17, 2024

The first was becoming one of the first research companies to move its panels and surveys online, reducing costs and increasing the speed and scope of data collection. Artificial Intelligence, CIO, Cloud Computing, Cloud Management, Digital Transformation, IT Leadership, Machine Learning, Microsoft Azure

Digital Transformation 116

Digital Transformation Dashboards Reporting Data Science 116

CIO Business Intelligence

APRIL 29, 2022

Preparing for an artificial intelligence (AI)-fueled future, one where we can enjoy the clear benefits the technology brings while also the mitigating risks, requires more than one article. This first article emphasizes data as the ‘foundation-stone’ of AI-based initiatives. Establishing a Data Foundation. era is upon us.

Data Governance 145

Data Governance IT Risk Data Lake 145

Cloudera

OCTOBER 11, 2022

A recent VentureBeat article , “4 AI trends: It’s all about scale in 2022 (so far),” highlighted the importance of scalability. The article goes on to share insights from experts at Gartner, PwC, John Deere, and Cloudera that shine a light on the critical role that data plays in scaling AI. . Data science needs analytics.

Snapshot 92

Snapshot Data Science Digital Transformation Metadata 92

Smart Data Collective

APRIL 25, 2022

Throughout this article it will be discussed in more detail how different departments in your company can benefit from using artificial intelligence to manage their online profile. Instead, machine learning algorithms can be much more effective when tracking online reviews. This is key when it comes to attracting new customers.

Management 135

Management Machine Learning Marketing Deep Learning 135

Analytics Vidhya

SEPTEMBER 13, 2022

This article was published as a part of the Data Science Blogathon. Introduction With technological evolution, data dependence is increasing much faster. Organizations are now employing data-driven approaches all over the world. One of the most widely used data applications […].

Predictive Analytics 261

Predictive Analytics Analytics Data-driven Data Science 261

Cloudera

AUGUST 17, 2020

One of the primary sources of that knowledge comes from our Knowledge Articles. These Knowledge Articles have proven to be invaluable to our Support Staff over the years. To that end, we have been working on improving the way our customers discover the collection of knowledge available in our Knowledge Articles.

Testing 86

Testing Machine Learning Interactive Metrics 86

TDAN

MAY 18, 2021

Language independence plays a significant role in the machine-learning of natural language processing (NLP). This is made possible with appropriate data training of AI to multiple language translation by minimizing the complexity of the data collection and […].

Machine Learning 52

Machine Learning Data Collection Technology IT 52

Domino Data Lab

MAY 8, 2019

Paco Nathan’s latest article features several emerging threads adjacent to model interpretability. I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. Introduction.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

IBM Big Data Hub

MARCH 27, 2024

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors.

Experimentation 77

Experimentation Modeling Deep Learning Data-driven 77

Smart Data Collective

MAY 1, 2022

Multiple emails, social media posts, blogs, articles, and other text forms are generated daily. This will eventually lead you to situations where you know that valuable data is inside these documents, but you cannot extract them. . Moreover, the data collected is not free from error or biases if humans handle it.

Cost-Benefit 116

Cost-Benefit Unstructured Data Machine Learning Marketing 116

IBM Big Data Hub

OCTOBER 16, 2023

By looking critically at these examples, and at successes in overcoming bias, data scientists can begin to build a roadmap for identifying and preventing bias in their machine learning models. Companies are motivated to tackle the challenge of bias in AI not only to achieve fairness, but also to ensure better results.

Advertising 72

Advertising Machine Learning Data Architecture Cost-Benefit 72

Cloudera

SEPTEMBER 4, 2020

Machine learning and AI are going to be critical for Communication Service Providers (CSPs)to succeed in the future as traditionally telcos have always been data-rich but insight poor. . The Future Of The Telco Industry And Impact Of 5G & IoT – Part 3. Hi Vijay, thank you so much for joining us again.

IoT 93

IoT Machine Learning Optimization Insurance 93

Cloudera

AUGUST 30, 2022

But while state and local governments seek to improve policies, decision making, and the services constituents rely upon, data silos create accessibility and sharing challenges that hinder public sector agencies from transforming their data into a strategic asset and leveraging it for the common good. . Towards Data Science ).

Data Architecture 78

Data Architecture Data Lake Metadata Data Warehouse 78

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch ’s “ Product Management for AI ”session at Rev provided a “crash course” on what product managers and leaders need to know about shipping machine learning (ML) projects and how to navigate key challenges. Be aware that machine learning often involves working on something that isn’t guaranteed to work.

Management 110

Management Machine Learning Experimentation Metrics 110

Occam's Razor

MARCH 30, 2017

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

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

Analytics Vidhya

MAY 19, 2019

This article was submitted as part of Analytics Vidhya’s Internship Challenge. The post Data Science Project: Scraping YouTube Data using Python and Selenium to Classify Videos appeared first on Analytics Vidhya. Introduction I’m an avid YouTube user. The sheer amount of content I can.

Data Science 303

Data Science Analytics Machine Learning Data Collection 303

FineReport

MARCH 24, 2024

Given the critical role they play, employers actively seek data analysts to enhance efficiency and stimulate growth. This article explores the data analyst job description, covering essential skills, tools, education, certifications, and experience.

Statistics 52

Statistics Data mining Visualization Reporting 52

CIO Business Intelligence

APRIL 14, 2022

This article was co-authored by Katherine Kennedy , an Associate at Metis Strategy. production assets with sensors to generate digitized methane detection data and indicate methane leaks, allowing them to improve safety measures onsite and lower emissions. Smarter operations through integrated data and analytics.

Strategy 110

Strategy Digital Transformation IoT Measurement 110

IBM Big Data Hub

AUGUST 4, 2023

When workers get their hands on the right data, it not only gives them what they need to solve problems, but also prompts them to ask, “What else can I do with data?” ” through a truly data literate organization. What is data democratization? The platform comprises three powerful components: the watsonx.ai

Data Architecture 62

Data Architecture Data Lake Machine Learning Data Governance 62