Occam's Razor

OCTOBER 14, 2014

See step four in the process for creating your Digital Marketing and Measurement Model.]. This recommendation also valuable for companies that have very unique business models, or face other unusual circumstances (geographic, size, amount of innovation, and many others). See Page 269. :). So how can you use your own data?

Key Performance Indicator 133

Key Performance Indicator Metrics Reporting Marketing 133

DMBS2

MAY 20, 2018

Multiple kinds of data model are viable … … but it’s usually helpful to be able to do some kind of JOIN. My two central examples have long been inaccurate metrics and false-positive alerts. Data(base) management technology is progressing pretty much as I expected. That ties into a number of areas of interest.

Internet of Things 50

Internet of Things Predictive Analytics Metrics Enterprise 50

Occam's Razor

JANUARY 2, 2013

It will be the same in 2013. Even if you never get into the mess of attribution modeling and all that other craziness, you are much smarter by just analyzing the data, and implications, from at this report. After that if you can't resist the itch, go play with the, now free to everyone, Attribution Modeling Tool in GA.

Strategy 159

Strategy Analytics Reporting Metrics 159

The Unofficial Google Data Science Blog

APRIL 23, 2024

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Sisense

MAY 26, 2020

While training a model for NLP, words not present in the training data commonly appear in the test data. Using the semantic meaning of words it already knows as a base, the model can understand the meanings of words it doesn’t know that appear in test data. It’s difficult to retrain models frequently from scratch for new data.

Unstructured Data 98

Unstructured Data Big Data Testing Machine Learning 98

Domino Data Lab

AUGUST 22, 2019

The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. While the field of computational linguistics, or Natural Language Processing (NLP), has been around for decades, the increased interest in and use of deep learning models has also propelled applications of NLP forward within industry.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Occam's Razor

APRIL 15, 2019

Bubble Kings most commonly reside in organizations where there is little to no accountability (or misplaced accountability, ex: celebration of vanity metrics). They bring up that one time in 2013 when your analysis missed an important assumption. You know my Care-Do-Impact model for analysis and storytelling.

Measurement 79

Measurement Strategy Data Processing Uncertainty 79

AWS Big Data

MARCH 13, 2024

For building any generative AI application, enriching the large language models (LLMs) with new data is imperative. Each service implements k-nearest neighbor (k-NN) or approximate nearest neighbor (ANN) algorithms and distance metrics to calculate similarity. You can track metrics from here. Waiting for connections.

Data Processing 111

Data Processing Dashboards Machine Learning Management 111

Domino Data Lab

APRIL 21, 2021

We’ll use a gradient boosting technique via XGBoost to create a model and I’ll walk you through steps you can take to avoid overfitting and build a model that is fit for purpose and ready for production. from sklearn import metrics. from sklearn import metrics. Data Ingestion & Exploratory Data Analysis.

Statistics 69

Statistics Machine Learning Modeling Metrics 69

Occam's Razor

AUGUST 9, 2016

Along the way I'll share some of my favourite metrics and analytics best practices that should accelerate your path to becoming a true Analysis Ninja. Gain Attribution Modeling Savvy. You can also search for other stuff, like custom reports or attribution models. Jump-Start Your Learning. Another tip. That's ok.

Analytics 109

Analytics Metrics Reporting Strategy 109

IBM Big Data Hub

FEBRUARY 22, 2024

Earning trust in the outputs of AI models is a sociotechnical challenge that requires a sociotechnical solution. There must be a concerted effort to make these principles a reality through consideration of the functional and non-functional requirements in the models and the governance systems around those models.

Metadata 92

Metadata Measurement Risk Modeling 92

Occam's Razor

DECEMBER 9, 2013

One that reflects the customer expectations of 2013. Or Ford (it is amazing that in 2013, for such an expensive product, it looks so… 2005). Bonus: Facebook Marketing: Best Metrics, ROI, Business Value ]. Don't worry about attribution modeling yet. Look at the colors. Look at the icons. Beat Motrin. Inform Me.

Marketing 165

Marketing Analytics Key Performance Indicator Optimization 165

CIO Business Intelligence

AUGUST 12, 2022

in 2013, Alfa Aesar in 2015, Affymetrix and FEI Co. We’re very much focused on the commercialization of acquisitions, making sure we don’t break the deal models and that things are running as they should be,” says John Stevens, vice president of IT at Thermo Fisher. in 2016, and BD Advanced Bioprocessing in 2018. Catalyzing change.

IT 105

IT Data Lake Sales Interactive 105

AWS Big Data

JULY 25, 2023

As their workload evolved, Alcion engineers tracked OpenSearch domain utilization via the provided Amazon CloudWatch metrics, making changes to increase storage and optimize their compute resources. This allowed Alcion to focus on optimizing the tenancy model for the new search architecture.

Cost-Benefit 73

Cost-Benefit Modeling Management Optimization 73

Occam's Razor

SEPTEMBER 21, 2015

First, someone worked really hard on this and created a really nice model for a smarter decision to be made for 2014. Second, between 2012 and 2013. When I present it, I'll say something like "Our peak investment, in Aquantive in 2013, was 700k." You are a Ninja, it will likely take you less. Rest is irrelevant.

Visualization 160

Visualization Key Performance Indicator Slice and Dice Strategy 160

Sisense

DECEMBER 11, 2019

He outlined how critical measurable results are to help VCs make major investment decisions — metrics such as revenue, net vs gross earnings, sales , costs and projections, and more. And he demonstrated how the Periscope Data platform overcomes the challenges of huge data volumes that can’t be easily modeled by traditional BI.

Data Lake 80

Data Lake Big Data Sales Data-driven 80

DataKitchen

JUNE 24, 2021

Chapin shared that even though GE had embraced agile practices since 2013, the company still struggled with massive amounts of legacy systems. One of the keys for our success was really focusing that effort on what our key business initiatives were and what sorts of metrics mattered most to our customers.

ROI 211

ROI Metrics Measurement Cost-Benefit 211

Ontotext

MARCH 24, 2021

For these reasons, we have applied semantic data integration and produced a coherent knowledge graph covering all Bulgarian elections from 2013 to the present day. A set of of sample queries is provided to help the understanding of the data model and shorten the learning curve. Easily accessible linked open elections data.

Statistics 142

Statistics Data Processing Publishing Metrics 142

Occam's Razor

APRIL 29, 2013

[A benchmark for you: In 2013 if 30% of your time, Ms./Mr. Many used some data, but they unfortunately used silly data strategies/metrics. And silly simply because as soon as the strategy/success metric being obsessed about was mentioned, it was clear they would fail. It is a really good metric. They get you fired.

Marketing 166

Marketing Metrics Advertising Measurement 166

Jet Global

MAY 1, 2023

Companies like Tableau (which raised over $250 million when it had its IPO in 2013) demonstrated an unmet need in the market. As a result, end users can better view shared metrics (backed by accurate data), which ultimately drives performance. Pricing model: The pricing scale is dependent on several factors.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52