Data Science and Beyond

JANUARY 11, 2020

When I started my PhD in 2009, the plan was to work on sentiment analysis of opinion polls. I learned about Bayesian statistics and conjugate priors. What can one do to remain relevant in such an environment? Read this post to find out. Highlights from my past. Moving forward in my PhD, I got into topic modelling.

Software 103

Software Data Science Machine Learning Deep Learning 103

Peter James Thomas

AUGUST 12, 2018

Integrity of statistical estimates based on Data. Having spent 18 years working in various parts of the Insurance industry, statistical estimates being part of the standard set of metrics is pretty familiar to me [7]. The thing with statistical estimates is that they are never a single figure but a range. million ± £0.5

Metrics 49

Metrics Statistics Data Quality Measurement 49

Peter James Thomas

APRIL 9, 2019

Overall the total number of articles and new pages I published exceeded 2017’s figures to claim the second spot behind 2009; our first year in business. Statistics & Data Science. Statistics & Data Science. These are as follows: General Data Articles. Data Visualisation. CDO perspectives. Programme Advice.

Data-driven 49

Data-driven Statistics Big Data Data Science 49

Domino Data Lab

APRIL 21, 2021

In contrast, the decision tree classifies observations based on attribute splits learned from the statistical properties of the training data. Machine Learning-based detection – using statistical learning is another approach that is gaining popularity, mostly because it is less laborious. 3f" % x) dataDF.describe().

Statistics 69

Statistics Machine Learning Modeling Metrics 69

The Unofficial Google Data Science Blog

JULY 11, 2017

SCOTT Time series data are everywhere, but time series modeling is a fairly specialized area within statistics and data science. They may contain parameters in the statistical sense, but often they simply contain strategically placed 0's and 1's indicating which bits of $alpha_t$ are relevant for a particular computation. by STEVEN L.

Forecasting 64

Forecasting Statistics Modeling Software 64

Sisense

MARCH 20, 2019

What our data engineers like about this course is that it is geared towards the data scientists and covers practical issues for statistical computing. Apache Spark : This unified analytics engine for Big Data processing was created in 2009 as a replacement for MapReduce. This keeps you focused on what the data scientists need from you.

Big Data 72

Big Data Machine Learning Data Warehouse Unstructured Data 72

Domino Data Lab

JUNE 8, 2021

The intuition here is that a decision boundary that leaves a wider margin between the classes generalises better, which leads us to the key property of support vector machines — they construct a hyperplane in a such a way that the margin of separation between the two classes is maximised (Haykin, 2009). Derivation of a Linear SVM. Fisher, R.

Optimization 76

Optimization Machine Learning Measurement Data Science 76

Occam's Razor

MAY 14, 2012

eBay's green line is very close the performance of the category (and you'll see that often at peaks in the shopping category queries, eBay actually does worse starting holiday season 2009). The tussle between Wal-Mart and Target is interesting. Amazon is an interesting example.

Measurement 128

Measurement Analytics Advertising Marketing 128

bridgei2i

MAY 26, 2020

You know the markets shake and the accompanying Swine Flu epidemic of 2015 and 2016, the Japanese tsunami and the Thailand floods in 2011 that shook up the high-tech value chain quite a bit, the great financial crisis and the accompanying H1N1 outbreak in 2008-2009, MERS and SARS before that in 2003.

Enterprise 131

Enterprise Management Forecasting Manufacturing 131

Peter James Thomas

JUNE 20, 2019

Of course it can be argued that you can use statistics (and Google Trends in particular) to prove anything [1] , but I found the above figures striking. Feel free to substitute Data Lake for Data Warehouse if you want a more modern vibe, sadly it won’t change the failure statistics. . [5]. – McKinsey 2009. . [6].

Cost-Benefit 55

Cost-Benefit Data Warehouse Consulting Data Science 55

Edwin Chen

JANUARY 7, 2013

— Janis Krums (@jkrums) January 15, 2009. Behind the scenes: we run a Storm topology that tracks statistics on search queries. Consider, for example, what happened when Flight 1549 crashed in the Hudson. link] - There’s a plane in the Hudson. I’m on the ferry going to pick up the people.

Statistics 73

Statistics Machine Learning Advertising Metadata 73

The Unofficial Google Data Science Blog

MARCH 13, 2017

Typically, causal inference in data science is framed in probabilistic terms, where there is statistical uncertainty in the outcomes as well as model uncertainty about the true causal mechanism connecting inputs and outputs. 2009, " Measuring invariances in deep networks ". Technical Report 1341, University of Montreal, 2009.

IT 68

IT Visualization Modeling Uncertainty 68

Domino Data Lab

MAY 8, 2019

They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have. Use of influence functions goes back to the 1970s in robust statistics. evaluate the effects of models on human subjects. measure the subjects’ ability to trust the models’ results.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Occam's Razor

SEPTEMBER 29, 2009

Ideally you'll measure the number prior to your branding campaign, say Feb 2009, and then you'll measure it again during your campaign, March 2009. It shows which terms (hence brands, sites, properties) have risen the by the most statistically significant amounts. Notice the competitive trends?

Measurement 128

Measurement Metrics Analytics Marketing 128

Peter James Thomas

OCTOBER 1, 2019

Some authorities describe them as any diagram using a map to display statistical data; I cover this type of general chart in Map Charts below. The inimitable Randall Munroe of xkcd.com [7] explains this pithility as follows: | © Randall Munroe, xkcd.com (2009) | Excerpted from: Extrapolating |. Cartograms.

Sales 61

Sales Measurement Statistics Data Architecture 61

Occam's Razor

FEBRUARY 22, 2010

For example, with Alexa , you can report on traffic statistics (such as rank and page views), upstream (where your traffic comes from) and downstream (where people go after visiting your site) statistics, and key-words driving traffic to a site. You'll find other reports in the Resource Center.

Metrics 123

Metrics Advertising Reporting Software 123

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

On the one hand, basic statistical models (e.g. by TAMAN NARAYAN & SEN ZHAO A data scientist is often in possession of domain knowledge which she cannot easily apply to the structure of the model. linear regression, trees) can be too rigid in their functional forms. References Wightman, L. LSAC National Longitudinal Bar Passage Study.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

Occam's Razor

APRIL 8, 2013

Remember that the raw number is not the only important part, we would also measure statistical significance. By late 2009, that experiment was a success, too; they'd climbed back up to 4.5 The result? The properties with professional photography had 2-3 times the number of bookings! The graph is impressive, right?

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

Domino Data Lab

JULY 9, 2019

When he retired in 2009 he had some time on his hands. ” And this is one of his papers about “you’re doing it wrong” where he talked about the algorithmic culture that he was observing in the machine learning community versus the generative model community that was more traditional in statistics.

Data Science 112

Data Science Machine Learning Advertising Modeling 112