9 Best Articles in 2021
Interaction Design Foundation (IxDF)
Heuristic Evaluation: How to Conduct a Heuristic Evaluation
Interaction Design Foundation (IxDF)
9 min read · From 2016 · Learn to conduct a heuristic evaluation on any given user interface design. This article will teach you how to generate and conduct your own heuristic evaluations so you can improve the usability,…
visual-design.net
A Practical Guide to Linear Regression
visual-design.net
~15 min read · Sep 18th · From EDA to Feature Engineering to Model Evaluation
Sebastian Raschka
Model evaluation, model selection, and algorithm selection in machine learning
Sebastian Raschka
20+ min read · From 2018 · A single-PDF version of Model Evaluation parts 1-4 is available on arXiv: https://arxiv.org/abs/1811.12808
Demis Hassabis
AlphaZero: Shedding new light on the grand games of chess, shogi and Go
Demis Hassabis
7 min read · From 2018 · We introduce a full evaluation of AlphaZero, published in the journal Science, which describes a single algorithm that taught itself from scratch how to master the games of chess, shogi (Japanese…
turbinehq.com
The ultimate blueprint for creating a vendor evaluation system
turbinehq.com
7 min read · From 2016 · If vendors are causing problems in your purchasing, follow this blueprint for an effective vendor evaluation system and build a healthy vendor roster.
Inc.
How to Know If You're the Right Person to Pursue Your Business Idea
Inc.
2 min read · 2020-07-21 · As an advisor to entrepreneurs, one of the most common requests I get is for an evaluation of their next startup idea.
nealcabage.com
Opportunity Heuristics
nealcabage.com
8 min read · 2019-11-28 · A Scorecard-Based approach to Opportunity Evaluation A few years ago, I found myself doing a lot of research in order to identify startup opportunities to pursue. I built and sold a couple of…
nanonets.com
Health Checks for Machine Learning - A Guide to Model Retraining and Evaluation
nanonets.com
~12 min read · 2020-04-26 · Machine Learning in production is exponentially more difficult than offline experiments. In this blog we talk about model evaluation, maintenance and retraining.
Trending
visual-design.net
A Practical Guide to Linear Regression
visual-design.net
~15 min read · Sep 18th · From EDA to Feature Engineering to Model Evaluation
Ness Labs
Fear of judgement: why we are afraid of being judged
Ness Labs
5 min read · Oct 1st · If you have ever worried that poor performance in an evaluation will lead to a friend or colleague developing a negative opinion of you, then you are not alone. Fear of judgement by others is common.
blogs.sas.com
Causal inference and policy evaluation with deep neural networks
blogs.sas.com
8 min read · Sep 15th · In this post, I will introduce the new DEEPCAUSAL procedure in SAS Econometrics for causal inference and policy evaluation.
medrxiv.org
Causal and Associational Linking Language From Observational Research and Health Evaluation Literature in Practice: A systematic language…
medrxiv.org
Aug 30th · Background: Avoiding "causal" language with observational study designs is common publication practice, often justified as being a more cautious approach to interpretation. Objectives: We aimed to i) estimate the degree to which causality was implied by both the language linking exposures to outcomes and by action recommendations in the high-profile health literature, ii) examine disconnects between language and recommendations, iii) identify which linking phrases were most common, and iv) generate estimates by which these phrases imply causality. Methods: We identified 18 of the most prominent general medical/public health/epidemiology journals, and searched and screened for articles published from 2010 to 2019 that investigated exposure/outcome pairs until we reached 65 non-RCT articles per journal (n=1,170). Two independent reviewers and an arbitrating reviewer rated the degree to which they believed causality had been implied by the language in abstracts based on written guidance. Reviewers then rated causal implications of linking words in isolation. For comparison, additional review was performed for full texts and for a secondary sample of RCTs. Results: Reviewers rated the causal implication of the sentence and phrase linking the exposure and outcome as None (i.e., makes no causal implication) in 13.8%, Weak in 34.2%, Moderate in 33.2%, and Strong in 18.7% of abstracts. Reviewers identified an action recommendation in 34.2% of abstracts. Of these action recommendations, reviewers rated the causal implications as None in 5.3%, Weak in 19.0%, Moderate in 42.8% and Strong in 33.0% of cases. The implied causality of action recommendations was often higher than the implied causality of linking sentences (44.5%) or commensurate (40.3%), with 15.3% being weaker. The most common linking word root identified in abstracts was "associate" (n=535/1,170; 45.7%) (e.g. "association," "associated," etc). There were only 16 (1.4%) abstracts using "cause" in the linking or modifying phrases. Reviewer ratings for causal implications of word roots were highly heterogeneous, including those commonly considered non-causal. Discussion: We found substantial disconnects between causal implications used to link an exposure to an outcome and the action implications made. This undercuts common assumptions about what words are often considered non-causal and that policing them eliminates causal implications. We recommend that instead of policing words, editors, researchers, and communicators should increase efforts at making research questions, as well as the potential of studies to answer them, more transparent.
### Competing Interest Statement
The authors have declared no competing interest.
### Clinical Protocols
<https://osf.io/jtdaz/>
### Funding Statement
No funding was granted specifically for the support of this study, and no funders had any role in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication. The researchers were independent from funders and that all authors, external and internal, had full access to all of the data (including statistical reports and tables) in the study and can take responsibility for the integrity of the data and the accuracy of the data analysis is also required.
### Author Declarations
I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.
Yes
The details of the IRB/oversight body that provided approval or exemption for the research described are given below:
Not human subjects research
All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.
Yes
I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).
Yes
I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.
Yes
All data and code are publicly available through our OSF repository: https://osf.io/jtdaz, except for files containing personal identifying information and/or personal API keys.
<https://osf.io/jtdaz>
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UX Collective
Heuristic Analysis for UX — How to Run a Usability Evaluation
UX Collective
9 min read · From 2018 · Design is an investment, not an expense. At the risk of stating the obvious: It’s not enough to design a nice-looking product; it also has…
Ness Labs
Fear of judgement: why we are afraid of being judged
Ness Labs
5 min read · Oct 1st · If you have ever worried that poor performance in an evaluation will lead to a friend or colleague developing a negative opinion of you, then you are not alone. Fear of judgement by others is common.
medium.com
Cryptoassets: A crowd sourced evaluation & due diligence framework
medium.com
3 min read · From 2017 · Cryptoland still feels like the wild, wild west on many levels. Entrepreneurs planning to tokenize their business model and raise funds…
UX Collective
Design Interviewing: Ask Me Anything
UX Collective
20+ min read · From 2019 · A few months ago, I tweeted asking if people had questions about design interviewing. The interview and evaluation process can often feel…
Facebook AI
Dynaboard: Moving beyond accuracy to holistic model evaluation in NLP
Facebook AI
8 min read · May 24th · We're introducing Dynaboard, an evaluation-as-a-service platform for conducting comprehensive evaluations of NLP models.
webaim.org
The WebAIM Million - An accessibility analysis of the top 1,000,000 home pages
webaim.org
10 min read · From 2019 · Home > WebAIM Projects > The WebAIM Million In February 2019, WebAIM conducted an evaluation of the home pages for the top 1,000,000 web sites using the WAVE stand-alone API (with additional tools to…
VentureBeat
Google’s AI picks which machine learning models will produce the best results
VentureBeat
2 min read · From 2019 · Google AI researchers propose a new machine learning model technique that treats evaluation as a binary classification problem.
blog.acolyer.org
Statistically rigorous Java performance evaluation
blog.acolyer.org
20+ min read · From 2017 · Statistically rigorous Java performance evaluation Georges et al., OOPSLA’07 This paper won the 10-year most influential paper award at OOPSLA this year. Many of the papers we look at on this blog …
HackerNoon
The Da Vinci Schedule — How to Organize Your Day and Week for Peak Performance
HackerNoon
7 min read · From 2017 · At the moment, I am working on multiple projects and I identified that structure and proper evaluation of psychological and physiological…
