How To “Ultralearn” Data Science: deep understanding and experimentation, Part 4

KDnuggets

2019 Dec Opinions Advice Data Science Experimentation Ultralearn

Experimentation and Testing: A Primer

Occam's Razor

This post is a primer on the delightful world of testing and experimentation (A/B, Multivariate, and a new term from me: Experience Testing). It is important to realize that experimentation and testing might sound big and complex but it is not.

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How To “Ultralearn” Data Science: summary, for those in a hurry

KDnuggets

For those of you in a hurry and interested in ultralearning (which should be all of you), this recap reviews the approach and summarizes its key elements -- focus, optimization, and deep understanding with experimentation -- geared toward learning Data Science.

Six Nudges: Creating A Sense Of Urgency For Higher Conversion Rates!

Occam's Razor

Marketing Tips Usability Voice of Customer conversion rate experimentation and testing user experienceBy every indicator available, ecommerce is continuing to grow at an insane speed.

Driving Discovery and Experimentation in your Organization

Speaker: Teresa Torres, Product Discovery Coach, Product Talk, David Bland, Founder and CEO, Precoil, and Hope Gurion, Product Coach and Advisor, Fearless Product LLC

If you want to build what matters, you can't move forward blindly. But to make progress, you can't let things slow to a crawl while you focus resources on gathering data. This is where continuous discovery and experimentation come in. Join Teresa Torres (Product Discovery Coach, Product Talk), David Bland (Founder, Precoil), and Hope Gurion (Product Coach and Advisor, Fearless Product) in a panel discussion as they cover how - and why - to build a culture of discovery and experimentation in your organization.

Corinium Meets: Quantum Metric Head of Behavioural Research Marina Shapira

Corinium

Ahead of her presentation at CDAO UK, we spoke with Quantum Metric’s Marina Shapira about predictive analytics, why companies should embrace a culture of experimentation how and CAOs and CXOs can work together effectively.

The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

Advanced Analytics Big Data Digital Analytics Web Analytics Web Insights Web Metrics actionable analytics business optimization experimentation and testing key performance indicators This should not be news to you.

Measuring Incrementality: Controlled Experiments to the Rescue!

Occam's Razor

Having read this post what might be the biggest downside to experimentation? Advanced Analytics Marketing Tips Search Engine Marketing acquisition portfolio optimization actionable web analytics excellent analytics tips experimentation and testing

Experiment or Die. Five Reasons And Awesome Testing Ideas.

Occam's Razor

There is a tendency to think experimentation and testing is optional. So as my tiny gift for you here are five experimentation and testing ideas for you. This recession season buy your CEO the gift that keeps giving, a experimentation and testing tool.

Eight Silly Data Things Marketing People Believe That Get Them Fired.

Occam's Razor

competitive intelligence Digital Analytics Digital Marketing Marketing Tips Search Engine Marketing Social Media Web Metrics actionable web analytics digital marketing experimentation and testing marketing metrics

IBM expands data and AI excellence with data cataloging technology in Cloud Pak for Data

IBM Big Data Hub

Describing the breadth of IBM's leadership and experimentation in the data and AI space is no small task. IBM has been working with more than 200 production blockchain networks , thousands of regulatory documents and datasets across industries, and hundreds of AI research projects

How to apply machine learning and deep learning methods to audio analysis

KDnuggets

Find out how data scientists and AI practitioners can use a machine learning experimentation platform like Comet.ml to apply machine learning and deep learning to methods in the domain of audio analysis. 2019 Nov News Audio Machine Learning Speech Recognition

Industrializing your AI and data science models with IBM Cloud Private for Data

IBM Big Data Hub

The next chapter is all about moving from experimentation to true transformation. Companies are entering “chapter two” of their digital transformation. It’s about gaining speed and scale.

Establishing More Trust In 2020 With Blockchain

DataFloq

In the last decade, blockchain has garnered the attention of technologists, entrepreneurs and industry stalwarts, leading to experimentation and exploration. 2020 is here.

Quantum Computing and Blockchain: Facts and Myths

DataFloq

Google states that its experiment is the first experimental challenge against the extended Church-Turing thesis — also known as computability thesis — which claims that traditional computers can effectively carry out any “reasonable” model of computation.

Don’t Just Sit There, Experiment!

Decision Management Solutions

Randomly select groups of customers and use the experimental approach on them, to prevent bias, and ensure a clean test Keep information on both groups – what you would normally do and what you experimented on – so you can compare the approaches later.

The 12 Rules of DataOps to Avert a DataOops

Kirk Borne

This can be overcome with small victories (MVP minimum viable products, or MLP minimum lovable products) and with instilling ( i.e., encouraging and rewarding) a culture of experimentation across the organization. DataOps accepts a fail-fast, learn-fast culture of experimentation.

Machine Learning Product Management: Lessons Learned

Domino Data Lab

Pete indicates, in both his November 2018 and Strata London talks, that ML requires a more experimental approach than traditional software engineering. These steps also reflect the experimental nature of ML product management.

When adopting machine learning, people are as important as technology

Cloudera

Integrating the capability into your organization requires operational transformation and lots (and lots) of experimentation. . An SME can play a critical role in your team at the onset of experimentation.

Apply Modern CRM Dashboards & Reports Into Your Business – Examples & Templates

datapine

When we say “optimal design,” we don’t mean cramming piles of information into one space or being overly experimental with colors. Niche or industry aside, it’s likely that your customers are the beating heart of your entire operation.

How Analytics by Design Tackles The Yin and Yang of Metrics and Data

Kirk Borne

By applying an agile methodology, we are able to adopt a culture of experimentation that permits us to fail fast in order to learn fast and that delivers both the minimum viable product and the minimum lovable product. Written by Dr. Kirk Borne.

On the Hunt for Patterns: from Hippocrates to Supercomputers

Ontotext

This will level up the processes of observation, experimentation and analysis, which are fundamental for medicine.

Announcing Domino 3.3: Datasets and Experiment Manager

Domino Data Lab

Data science is different from other workstreams like software development in that it involves open-ended exploration and experimentation to find optimal solutions. Our mission at Domino is to enable organizations to put models at the heart of their business.

Interview with: Sankar Narayanan, Chief Practice Officer at Fractal Analytics

Corinium

It is also important to have a strong test and learn culture to encourage rapid experimentation. Will you please describe your role at Fractal Analytics? I am the Chief Practice Officer for Insurance, Healthcare, and Hi-Tech verticals at Fractal.

AI in Analytics: The NLQ Use Case

Sisense

When the app is first opened, the user may be searching for a specific song that was heard while passing by the neighborhood cafe, or the user may want to be surprised with, let’s say, a song from the new experimental album by a Yemen Reggae folk artist.

The challenges you’ll face deploying machine learning models (and how to solve them)

Cloudera

This will enable your teams to move ML models from experimentation to production faster, and give you streamlined insights into the performance of your mathematical and technical metrics. . In 2019, organizations invested $28.5

Misadventures in experiments for growth

The Unofficial Google Data Science Blog

by MICHAEL FORTE Large-scale live experimentation is a big part of online product development. This means a small and growing product has to use experimentation differently and very carefully. This blog post is about experimentation in this regime.

Evaluating Ray: Distributed Python for Massive Scalability

Domino Data Lab

for model serving (experimental), are implemented with Ray internally for its scalable, distributed computing and state management benefits, while providing a domain-specific API for the purposes they serve.

Ask Why! Finding motives, causes, and purpose in data science

Data Science and Beyond

Causality and experimentation. Some people equate predictive modelling with data science, thinking that mastering various machine learning techniques is the key that unlocks the mysteries of the field. However, there is much more to data science than the What and How of predictive modelling.

12 Marketing Reports Examples You Can Use For Annual, Monthly, Weekly And Daily Reporting Practice

datapine

A daily marketing report will also allow you for faster experimentation: running small operations to answer small questions. Let’s face it: every serious business that wants to generate leads and revenue needs to have a marketing strategy that will help them in their quest for profit.

Drug Discovery Needs AI To Discover More Treatments

Smart Data Collective

The greatest advantage of AI is that it can digest vast amounts of medical knowledge — from thousands of published reports and scientific papers, say — and devise novel predictions and formulations that would take human researchers years of inefficient experimentation to find.

Managing Risk in Data Projects

Dataiku

It’s probably safe to say that for at least some of those explorers, the prospect of risk when it comes to data and AI projects is paralyzing, causing them to stay in a phase of experimentation.

Keynote Takeaways From Gartner Data & Analytics Summit

Sisense

Gartner chose to group the rest of the keynote into three main messages according to the following categories: Here are some of the highlights as presented for each of them: Data Driven – “Adopt an Experimental Mindset”.

Is Artificial Intelligence Revolutionizing Environmental Health?

Simply Statistics

Concurrently, while population data are booming, toxicology is creating a variety of experimental models to advance our understanding of how chemicals and environmental exposures may pose risks to human health. NOTE: This post was written by Kevin Elliott, Michigan State University; Nicole Kleinstreuer, National Institutes of Health; Patrick McMullen, ScitoVation; Gary Miller, Columbia University; Bhramar Mukherjee, University of Michigan; Roger D.

Is Google Cloud Platform Ready to Run Your Data Analytics Pipeline?

Sanjeev Mohan

GCP has gained acceptance for development and experimentation and more enterprise customers are putting it into production. Is Google Cloud Platform Ready to Run Your Data Analytics Pipeline? This is the focus of my latest research which published in Jan 2019.

Methods of Study Design – Experiments

Data Science 101

Some pitfalls of this type of experimentation include: Suppose an experiment is performed to observe the relationship between the snack habit of a person while watching TV. Bias can cause a huge error in experimentation results so we need to avoid them.

Hey Siri, What’s My Forecasted EBITDA Look Like?

Jedox

Experimental” Technology. Is AI truly experimental technology? Even though we have so much advanced technology surrounding us, we still cannot just ask, “ Hey Siri, what’s my forecasted EBITDA look like ?” There are many reasons why such technology isn’t available yet—insufficient data, unstructured data and some human knowledge that is not yet transferable to machine.

The Role of Theory in Data Analysis

Simply Statistics

Many data analysts are not involved in the data collection process or the experimental design and so it is important to inquire about he process by which the data came to them. But when she visited the lab one day to see how the experiments were done, she discovered that the experimental units were all processed in one batch and the control units were all processed in a different batch at a different time, thereby confounding any treatment effect with the batch.

Expert Speak | Transforming Digital Enterprises

bridgei2i

With increasing mainstream acceptance and adoption of AI-led technologies, C-suite executives today have gone beyond committing ‘digital experimentation’ to large scale Digital Transformation, be it pan-enterprise or functional.

Apache YuniKorn (Incubating) 0.8 release: What’s new and upcoming?

Cloudera

All the tests are done with Kubemark , a tool that helps us to simulate large K8s clusters and run experimental workloads. Recap: What is YuniKorn Scheduler.

Open Data Science and Machine Learning for Business with Cloudera Data Science Workbench on HDP

Cloudera

Data scientists require on-demand access to data, powerful processing infrastructure, and multiple tools and libraries for development and experimentation.

Augmented Data Discovery Provides Users with Crucial Answers

Smarten

Advanced Data Discovery ensures data democratization and can drastically reduce the time and cost of analysis and experimentation. Advanced Data Discovery Can and Should Be Available to All!

Predictive Analytics Can Guide the Organization to Success

Smarten

Plug n’ Play Predictive Analysis for Accurate Forecasting! There are numerous considerations when a business looks at upgrading or acquiring an analytical solution. One very important capability is Put n’ Play predictive analysis.