AWS Big Data

JUNE 28, 2023

Challenges Customers across industries today are looking to increase revenue and customer engagement by implementing near-real time analytics use cases like personalization strategies, fraud detection, inventory monitoring, and many more. They would like to get these metrics in near-real time using a zero-ETL integration. or higher).

Data Warehouse 85

Data Warehouse Analytics Metrics Dashboards 85

AWS Big Data

MARCH 11, 2024

Make sure that data is flowing into your MSK topic using Amazon CloudWatch metrics (for example, BytesOutPerSec ). Set up streaming ingestion To set up streaming ingestion, complete the following steps: Set up the AWS Identity and Access Management (IAM) role and trust policy required for streaming ingestion.

Analytics 67

Analytics Data Warehouse Optimization Metrics 67

The Unofficial Google Data Science Blog

JUNE 30, 2016

It should be noted that inverse probability weighting is not generally optimal (i.e., We do this by describing the methods in terms of loss functions whose expectation is optimized at the true value of the propensity score. the curse of dimensionality).

Statistics 44

Statistics Optimization Modeling Experimentation 44

AWS Big Data

MARCH 21, 2024

Challenges Customers across industries today are looking to use data to their competitive advantage and increase revenue and customer engagement by implementing near real time analytics use cases like personalization strategies, fraud detection, inventory monitoring, and many more. For DB instance identifier , enter zero-etl-source-rms.

Data Warehouse 88

Data Warehouse Metrics Statistics Optimization 88

The Unofficial Google Data Science Blog

AUGUST 27, 2019

This problem can be phrased as an optimization problem — given some fixed review capacity how should we sample videos? Of course, any mistakes by the reviewers would propagate to the accuracy of the metrics, and the metrics calculation should take into account human errors.

Metrics 98

Metrics Statistics Uncertainty Optimization 98

Occam's Razor

DECEMBER 3, 2012

We like to believe that all there is to digital marketing is to do some search engine optimization, send out an email blast every once in a while, get our agency to create a flash-heavy "brand experience" website, or slap together a mobile app in the corporate-approved shade of eggshell white. Is Your Digital Strategy Magnificent?

Marketing 147

Marketing Advertising Strategy Optimization 147

Cloudera

NOVEMBER 17, 2021

There’s recognition that it’s nearly impossible to find the unicorn data scientist that was the apple of every CEO’s eye in 2012. TPOT is a library for performing sophisticated search over whole ML pipelines, selecting preprocessing steps and algorithm hyperparameters to optimize for your use case. Train Gensim’s Word2Vec.

Machine Learning 121

Machine Learning Visualization Data Science Metrics 121

Domino Data Lab

APRIL 21, 2021

from sklearn import metrics. There are different approaches to this strategy, with the two most commonly used being random oversampling and SMOTE. First, we define a function that will perform a grid search for the optimal hyperparameters of the classifier. from imblearn.over_sampling import SMOTE. from datetime import datetime.

Statistics 69

Statistics Machine Learning Modeling Metrics 69

AWS Big Data

MAY 19, 2023

Analytics professionals are tasked with deriving value from data stored in these distributed systems to create better, secure, and cost-optimized experiences for their customers. Orchestrating the run of and managing dependencies between these components is a key capability in a data strategy.

Machine Learning 84

Machine Learning Metrics Management Big Data 84

Occam's Razor

SEPTEMBER 21, 2015

The Directors, the Marketers, the Optimization employees and our resident social media gurus. We are going to discuss a cluster of strategies you can use to ensure that you present your message with radical simplicity and with an incredible focus. Don't underestimate the value of this strategy in your storytelling.

Visualization 160

Visualization Key Performance Indicator Slice and Dice Strategy 160

Domino Data Lab

MARCH 3, 2019

What metrics are used to evaluate success? While image data has been the stalwart for deep learning use cases since the proverbial “ AlexNet moment ” in 2011-2012, and a renaissance in NLP over the past 2-3 years has accelerated emphasis on text use cases, we note that structured data is at the top of the list in enterprise.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Sisense

DECEMBER 11, 2019

An exciting slate of presentations took them on a journey from why to how they should use data analytics to optimize their operations successfully and maximize their business opportunities. Ziv Ben Naim, Client Services Analytics & Strategy Lead, AppsFlyer Maayan Dukas Kfir, Data Analyst, AppsFlyer. The impact on customers.

Data Lake 80

Data Lake Big Data Sales Data-driven 80

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

With more features come more potential post hoc hypotheses about what is driving metrics of interest, and more opportunity for exploratory analysis. Looking at metrics of interest computed over subpopulations of large data sets, then trying to make sense of those differences, is an often recommended practice (even on this very blog).

Experimentation 61

Experimentation Testing Statistics Metrics 61