Cloudera

JANUARY 19, 2018

Before we get too far into 2018, let’s take a look at the ten most popular Cloudera VISION blogs from 2017. The blog finishes by providing concrete examples of how Cloudera customers are delivering strategic functionality like recommendation engines, predictive maintenance, and IoT workflows – all with machine learning at their core.

Machine Learning 45

Machine Learning IoT Big Data Insurance 45

Cloudera

DECEMBER 3, 2021

In part 1 of this blog post, we discussed the need to be mindful of data bias and the resulting consequences when certain parameters are skewed. For example, training an interview screening model using education data often contains gender information. As discussed in this article , model design can also be a source of bias too.

Uncertainty 98

Uncertainty Measurement Metrics Modeling 98

Cloudera

JULY 19, 2022

billion predicted for 2022. Historically, the evolution of a technology use, such as an increased adoption of digital financial services or the introduction of a new payment concept , has created an opening for illicit behaviors. Rules are informed by models that can be adjusted dynamically when new fraud schemes arise.

Predictive Analytics 83

Predictive Analytics Risk Machine Learning Measurement 83

Smarten

MAY 31, 2022

The technology research firm, Gartner has predicted that, ‘predictive and prescriptive analytics will attract 40% of net new enterprise investment in the overall business intelligence and analytics market.’ It is meant to identify crucial relationships and opportunities and risks and help the organization to accurately predict: Growth.

Predictive Analytics 67

Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 67

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. Will the model correctly determine it is a muffin or get confused and think it is a chihuahua? The extent to which we can predict how the model will classify an image given a change input (e.g. Model Visibility.

Machine Learning 82

Machine Learning Modeling Metadata Recreation/Entertainment 82

Smarten

JANUARY 10, 2024

Elon Musk recently announced the introduction of an artificial intelligence (AI) product to compete with the OpenAI ChatGPT product suite. Engaging Technology – It is perhaps no surprise that Musk decided to give his AI model a bit of a personality. with a 175 billion parameter training model and GPT 4 with 1.76

Marketing 52

Marketing Modeling IT Digital Transformation 52

FineReport

JUNE 11, 2021

Also, we will give a brief introduction of what business analysts should do and the tools often used for BI&A. As companies striving to embrace digital transformation and become data-driven, business intelligence and analytics skills and experience are essential to building a data-savvy team. Definition. BI Dashboard (by FineReport).

Business Intelligence 98

Business Intelligence Analytics Dashboards Statistics 98

Domino Data Lab

NOVEMBER 14, 2019

James Murdoch, Chandan Singh, Karl Kumber, and Reza Abbasi-Asi’s recent paper, “Definitions, methods, and applications in interpretable machine learning” Introduction. Model interpretability continues to spark public discourse among industry. Yet, Bin Yu, W. Why Iterate on the Definition of Interpretable ML?

Modeling 71

Modeling Machine Learning Data Science Experimentation 71

CIO Business Intelligence

SEPTEMBER 21, 2023

AI is now a board-level priority Last year, AI consisted of point solutions and niche applications that used ML to predict behaviors, find patterns, and spot anomalies in carefully curated data sets. Today’s foundational models are jacks-of-all-trades. According to McKinsey, gen AI is poised to add up to an annual $4.4

Enterprise 125

Enterprise Consulting Modeling Cost-Benefit 125

Cloudera

DECEMBER 20, 2022

The variable nature that fuels the renewable generation makes production less predictable. The variable nature that fuels the renewable generation makes production less predictable. With the right insights, energy production from renewable assets can be optimized and better predict the future of supply and demand.

Optimization 81

Optimization Data Analytics Analytics Cost-Benefit 81

Smarten

JUNE 8, 2022

Citizen Data Scientists can create new models, share models and collaborate, thereby improving business results and data literacy.’. What follows is a short list of sample use cases that leverage predictive analytics. Predicting Demand. Think of What Citizen Data Scientists Can Do to Help Your Business!

Predictive Analytics 52

Predictive Analytics Predictive Modeling Forecasting Optimization 52

Domino Data Lab

JANUARY 20, 2019

Introduction. What if there was a way to quantitatively measure whether your machine learning (ML) model reflects specific domain expertise or potential bias? What if there was a way to quantitatively measure whether your machine learning (ML) model reflects specific domain expertise or potential bias? That’s it.”.

Testing 63

Testing Modeling Machine Learning Data Science 63

Domino Data Lab

JULY 10, 2019

Introduction. This blog post considers Ludwig, offering a brief overview of the package and providing tips for practitioners such as when to use Ludwig’s command-line syntax and when to use its Python API. This blog also provides code examples with a Jupyter notebook that you can download or run via hosting provided by Domino.

Deep Learning 110

Deep Learning Visualization Recreation/Entertainment Data Processing 110

Domino Data Lab

MAY 1, 2019

This Domino Data Science Field Note provides highlights and excerpted slides from Chloe Mawer ’s “ The Ingredients of a Reproducible Machine Learning Model ” talk at a recent WiMLDS meetup. Introduction. Mawer is a Principal Data Scientist at Lineage Logistics as well as an Adjunct Lecturer at Northwestern University.

Machine Learning 81

Machine Learning Testing Data Science Modeling 81

IBM Big Data Hub

DECEMBER 4, 2023

   At its core, autonomous business planning comprises innovative methods that leverage the potential of cutting-edge technologies such as foundation models and generative AI. .     This is where autonomous planning shines. It empowers businesses in their sales planning, budgeting and forecasting processes.

Forecasting 51

Forecasting Finance Optimization Marketing 51

Cloudera

AUGUST 26, 2021

In this blog post, we will ingest a real world dataset into Ozone, create a Hive table on top of it and analyze the data to study the correlation between new vaccinations and new cases per country using a Spark ML Jupyter notebook in CML. Learn more about the impacts of global data sharing in this blog, The Ethics of Data Exchange.

Data Science 108

Data Science Forecasting Metadata Machine Learning 108

DataRobot Blog

JUNE 3, 2022

The influence of the GPT-3 language model has the potential to be both beneficial and misused. . Generative Pre-trained Transformer 3 (GPT-3) is a language model that utilizes deep-structured learning to predict human-like text. It was also fed the following introduction: “I am not a human. What is GPT-3?

Risk 52

Risk Predictive Modeling Modeling Technology 52

FineReport

JUNE 11, 2021

Also, we will give a brief introduction of what business analysts should do and the tools often used for BI&A. As companies striving to embrace digital transformation and become data-driven, business intelligence and analytics skills and experience are essential to building a data-savvy team. Definition. BI Dashboard (by FineReport).

Business Intelligence 52

Business Intelligence Analytics Dashboards Statistics 52

Cloudera

SEPTEMBER 20, 2022

Introduction. This blog is intended to serve as an ethics sheet for the task of AI-assisted comic book art generation, inspired by “ Ethics Sheets for AI Tasks.” AI-assisted comic book art generation is a task I proposed in a blog post I authored on behalf of my employer, Cloudera.

Deep Learning 86

Deep Learning Cost-Benefit Risk Data-driven 86

Alation

SEPTEMBER 7, 2021

This is the last of the 4-part blog series. In the previous blog , we discussed how Alation provides a platform for data scientists and analysts to complete projects and analysis at speed. In this blog we will discuss how Alation helps minimize risk with active data governance. Meet Governance Requirements.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

Cloudera

JUNE 7, 2021

In October of 2020 Cloudera acquired Eventador and Cloudera Streaming Analytics (CSA) 1.3.0 was released early in 2021. It was the first release to incorporate SQL Stream Builder (SSB) from the acquisition, and brought rich SQL processing to the already robust Apache Flink offering. Why batch + streaming?

Analytics 61

Analytics Manufacturing Measurement IoT 61

The Unofficial Google Data Science Blog

APRIL 17, 2017

Introduction Time series forecasting enjoys a rich and luminous history, and today is an essential element of most any business operation. Selection and aggregation of forecasts from an ensemble of models to produce a final forecast. So it should come as no surprise that Google has compiled and forecast time series for a long time.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

Sisense

OCTOBER 29, 2020

Over the years, some bold predictions have been made about the impact autonomous vehicles (AVs) will have on our daily lives. We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. It’s difficult not to get excited about this future. Baby steps for self-driving vehicles.

Machine Learning 90

Machine Learning Data Collection Cost-Benefit Advertising 90

AWS Big Data

JUNE 23, 2023

This blog post is co-written with Ori Nakar from Imperva. Redshift Serverless is ideal when it’s difficult to predict compute needs such as variable workloads, periodic workloads with idle time, and steady-state workloads with spikes. Imperva harnesses data to improve their business outcomes.

Data Lake 68

Data Lake Cost-Benefit Dashboards Data Warehouse 68

Alation

FEBRUARY 13, 2020

Expansion in our business model is driven by the number of users of the data catalog, which means that our average customer is virally successful relative to their initial investment. MunichRe’s data catalog sped the introduction of new, innovative data products to mitigate the risk of high impact crises caused by global warming.

Enterprise 52

Enterprise Data Lake Machine Learning Data-driven 52

Ontotext

NOVEMBER 22, 2020

If you wish to make an apple pie from scratch, you must first invent the universe. Carl Sagan, Cosmos. The quote above eloquently expresses the idea that even something as quotidian as an apple pie is the last link of a chain going back billions of years. You want to start at the very tip of the universe’s innovation.

Metadata 72

Metadata Cost-Benefit Unstructured Data Technology 72

Cloudera

FEBRUARY 8, 2023

I was looking for some broken code to add a workshop to our Spark Performance Tuning class and write a blog post about, and this fitted the bill perfectly. One such occurrence happened a few weeks ago when one of my colleagues was trying to make some churn analysis code downloaded from GitHub work. distinct().collect() distinct().collect()

Measurement 56

Measurement Testing Cost-Benefit ROI 56

Sisense

MAY 28, 2020

The cloud isn’t the future; it’s right now. In the Clouds is where we explore the ways cloud-native architecture, cloud data storage, and cloud analytics are changing key industries and business practices, with anecdotes from experts, how-to’s, and more to help your company excel in the cloud era. Saving lives in real-time.

Internet of Things 83

Internet of Things Metadata Data-driven Unstructured Data 83

datapine

MARCH 25, 2022

While some experts try to underline that BA focuses, also, on predictive modeling and advanced statistics to evaluate what will happen in the future, BI is more focused on the present moment of data, making the decision based on current insights. Table of Contents. 1) What Is Business Intelligence And Analytics? 6) BI And BA Examples.

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

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 108

Machine Learning Deep Learning Modeling Interactive 108

Domino Data Lab

JANUARY 6, 2019

Introduction. And my favorite topic: what are some of the best books, blogs, podcasts, etc., Also, clearly there’s no “one size fits all” educational model for data science. The Berkeley model addresses large university needs in the US. He is also the Co-Chair of the upcoming Data Science Leaders Summit, Rev.

Data Science 56

Data Science Machine Learning Reporting Visualization 56

Domino Data Lab

FEBRUARY 20, 2019

Introduction: Consider Being Product-Minded. Introduction: Consider Being Product-Minded. This blog post provides some excerpts from the discussion, the audio recording, as well as a full written transcript of the conversation. Applying Product Management Principles to Data Science.

Data Science 76

Data Science Testing Software Uncertainty 76

Cloudera

MAY 19, 2021

Introduction. In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. RAPIDS brings the power of GPU compute to standard Data Science operations, be it exploratory data analysis, feature engineering or model building. What is RAPIDS.

Machine Learning 137

Machine Learning Data Science Data Lake Modeling 137

Domino Data Lab

FEBRUARY 19, 2021

spaCy is a python library that provides capabilities to conduct advanced natural language processing analysis and build models that can underpin document analysis, chatbot capabilities, and all other forms of text analysis. brings many improvements to help build, configure and maintain your NLP models, including.

Enterprise 119

Enterprise Data Science Modeling Visualization 119

datapine

AUGUST 29, 2022

The saying “knowledge is power” has never been more relevant, thanks to the widespread commercial use of big data and data analytics. This trend has been brought about by the new demands of the modern marketplace, and it’s here to stay. The rate at which data is generated has increased exponentially in recent years. million searches per day and 1.2

Big Data 263

Big Data Data Analytics Analytics Data mining 263

AWS Big Data

JULY 12, 2023

This blog post is co-written with Zygimantas Koncius from Etleap. In this post, we explain how data teams can quickly configure low-latency data pipelines that ingest and model data from a variety of sources, using Etleap’s end-to-end pipelines with Amazon Redshift and dbt.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

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