Rocket-Powered Data Science

JULY 7, 2019

Computer Vision: Data Mining: Data Science: Application of scientific method to discovery from data (including Statistics, Machine Learning, data visualization, exploratory data analysis, experimentation, and more). NLG is a software process that transforms structured data into human-language content.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

Data Science and Beyond

APRIL 5, 2021

The initial covid-19 lockdown provided me with extra free time to make the measurement and offsetting of Automattic’s emissions from data centre power use happen. I previously posted about my experiences with RLS offline data collection and visualisation of the collected data , and have since helped with quite a few RLS surveys.

Experimentation 61

Experimentation Testing Publishing Measurement 61

Dataiku

APRIL 22, 2022

Enter Frugal AI , a technique that promises the use of less data and less compute power while guaranteeing robustness within the intended field of use for a given AI model.It In this blog series, we will explore Frugal AI from the perspectives of data, design, trust, and sustainability. It's All in a Name.

Experimentation 59

Experimentation Modeling Business Objectives Manufacturing 59

Cloudera

FEBRUARY 16, 2022

blueberry spacing) is a measure of the model’s interpretability. We can think of model lineage as the specific combination of data and transformations on that data that create a model. This maps to the data collection, data engineering, model tuning and model training stages of the data science lifecycle.

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

Occam's Razor

APRIL 8, 2013

We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. First, you figure out what you want to improve; then you create an experiment; then you run the experiment; then you measure the results and decide what to do.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

Insight

MARCH 12, 2020

In this article, I will discuss the construction of the AIgent, from data collection to model assembly. Data Collection The AIgent leverages book synopses and book metadata. The latter is any type of external data that has been attached to a book?—?for finished his first novel, Cuckoo’s Calling.

Modeling 59

Modeling Metadata Publishing Sales 59

O'Reilly on Data

MAY 14, 2020

AI PMs should enter feature development and experimentation phases only after deciding what problem they want to solve as precisely as possible, and placing the problem into one of these categories. Experimentation: It’s just not possible to create a product by building, evaluating, and deploying a single model.

Management 363

Management Experimentation B2B Machine Learning 363

Domino Data Lab

OCTOBER 2, 2019

This article covers causal relationships and includes a chapter excerpt from the book Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications by Andrew Kelleher and Adam Kelleher. As data science work is experimental and probabilistic in nature, data scientists are often faced with making inferences.

Machine Learning 68

Machine Learning Measurement Modeling Testing 68

Domino Data Lab

JUNE 23, 2019

Skomoroch proposes that managing ML projects are challenging for organizations because shipping ML projects requires an experimental culture that fundamentally changes how many companies approach building and shipping software. Yet, this challenge is not insurmountable. for what is and isn’t possible) to address these challenges.

Management 110

Management Machine Learning Experimentation Metrics 110

Ontotext

MAY 18, 2020

Ever since Hippocrates founded his school of medicine in ancient Greece some 2,500 years ago, writes Hannah Fry in her book Hello World: Being Human in the Age of Algorithms , what has been fundamental to healthcare (as she calls it “the fight to keep us healthy”) was observation, experimentation and the analysis of data.

Knowledge Discovery 72

Knowledge Discovery Experimentation Data-driven Metadata 72

Occam's Razor

JUNE 6, 2007

Experimentation & Testing (A/B, Multivariate, you name it). Benchmarking (exactly how you can do it), impactful actionable executive dashboards (what they should contain), creating a data driven organization. I am thrilled to say that my book Web Analytics: An Hour A Day has been published and is now widely available.

Analytics 60

Analytics Metrics Marketing Dashboards 60

Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. They’ve become “embedded institutions” in engineering. back to the structure of the dataset. intelligibility.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

FEBRUARY 4, 2019

We’ll unpack curiosity as a core attribute of effective data science, look at how that informs process for data science (in contrast to Agile, etc.), and dig into details about where science meets rhetoric in data science. That body of work has much to offer the practice of leading data science teams.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Occam's Razor

DECEMBER 12, 2016

Data quality plays a role into this. But, at the end of the day presence of a Tag Manager communicates to me that the company is serious about data collection and data quality. You'll be surprised, there's only one tool in that mix. It is not even an analytics tool. " That lead to this post.

Analytics 141

Analytics Data-driven Strategy Consulting 141

Occam's Razor

JULY 18, 2011

You just have to have the right mental model (see Seth Godin above) and you have to… wait for it… wait for it… measure everything you do! For everything you do it is important to measure your effectiveness of all three phases of your effort: Acquisition. You’re trying to measure how well you are doing to: Send emails.

Metrics 137

Metrics Marketing Measurement Cost-Benefit 137

Occam's Razor

SEPTEMBER 15, 2014

But why blame others, in this post let's focus on one important reason whose responsibility can be squarely put on your shoulders and mine: Measurement. Create a distinct mobile website and mobile app measurement strategies. Media-Mix Modeling/Experimentation. Still, let me try to surprise you. Many reasons.

Metrics 141

Metrics Reporting Analytics Marketing 141

Occam's Razor

MARCH 23, 2010

Too many new things are happening too fast and those of us charged with measuring it have to change the wheels while the bicycle is moving at 30 miles per hour (and this bicycle will become a car before we know it – all while it keeps moving, ever faster). Part of it fueled by Vendors. What a competitive bunch! This is sad.

Analytics 118

Analytics Consulting Metrics Experimentation 118

Cloudera

JUNE 6, 2019

Over time, workloads start processing more data, tenants start onboarding more workloads, and administrators (admins) start onboarding more tenants. While this approach provides isolation, it creates another significant challenge: duplication of data, metadata, and security policies, or ‘split-brain’ data lake.

Metadata 87

Metadata Data Lake Optimization Strategy 87

Occam's Razor

AUGUST 13, 2012

Yehoshua Coren: Best ways to measure user behavior in a multi-touch, multi-device digital world. What's possible to measure. What's not possible to measure. We all have smart phones, laptops, tablets and soon Smart TVs – but most of our measurements are usually done in Cookies that are device/browser specific.

Modeling 124

Modeling Metrics Data Quality Data-driven 124

Occam's Razor

OCTOBER 19, 2010

An expansive view of what it means to use data online, both from the type of data perspective and the kind of desired impact perspective. They'll simply puke data faster and, if you implement them right, more efficiently. What is the first thing you want when you think about web analytics? Of course tools. spectrum.

Analytics 135

Analytics Testing Measurement Optimization 135

Occam's Razor

MAY 27, 2015

In a recent set of keynotes and consulting engagements in the US, UK and Canada, I've had an overwhelming feeling that in very fundamental ways some companies make imprecise choices when it comes to their digital strategy. Not because they don't have enough money or opportunity or people. Let's go! Can you do RM+RP+RT using TV?

Marketing Analytics 153

Marketing Analytics Marketing Analytics Advertising 153

datapine

JANUARY 31, 2022

Because things are changing and becoming more competitive in every sector of business, the benefits of business intelligence and proper use of data analytics are key to outperforming the competition. BI software uses algorithms to extract actionable insights from a company’s data and guide its strategic decisions.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Occam's Razor

JANUARY 7, 2014

First… it is important to realize that big data's big imperative is driving big action. The organization functions off a clearly defined Digital Marketing & Measurement Model. #1. Remember none of these jobs will do any data collection/IT work, even in medium-sized companies.)

Data-driven 140

Data-driven Consulting Reporting Marketing 140

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

Implicitly, there was a prior belief about some interesting causal mechanism or an underlying hypothesis motivating the collection of the data. As computing and storage have made data collection cheaper and easier, we now gather data without this underlying motivation. We ought not dredge our data.

Experimentation 61

Experimentation Testing Statistics Metrics 61

Occam's Razor

APRIL 29, 2013

It turns out that Marketers, especially Digital Marketers, make really silly mistakes when it comes to data. Small data. Many used some data, but they unfortunately used silly data strategies/metrics. Real-time data is life changing. It seems absolutely stupid to say, " No, I don't want real-time data. "

Marketing 166

Marketing Metrics Advertising Measurement 166

Occam's Razor

OCTOBER 12, 2017

The tiny downside of this is that our parents likely never had to invest as much in constant education, experimentation and self-driven investment in core skills. Analytical thinking is a collection of skills. They never had to worry that they have to be in a persistent forward motion… sometimes just to stay current. This is normal.

Marketing 136

Marketing Analytics Machine Learning Strategy 136