Based on its recent analysis of the global smart data analytics solutions market, Frost & Sullivan recognizes Guavus (a Thales company) with the 2019 Global Enabling Technology Leadership Award.Read Full Story
Avora One Optimises Data Analysis Process by Reducing Time Spent on Data Processing and Enhances Decision Making Enabling Business Users to Quickly Find Answers to Their Questions
Based on its recent analysis of the European AI-based business intelligence solution market, Frost & Sullivan recognizes Avora with the 2019 European Technology Innovation Award for accelerating the data analytics proces
Editor’s Note: This analysis is featured in the GreenBook Market Leaders Report. The GreenBook Market Leaders Report is your #1 guide to brand success in the insights industry, featuring the U.S. Top 50, and in-depth analysis from leading CEOs. In its inaugural edition, you’ll learn who is in the lead, who is rising towards the top, and where your company fits into it all.Read Full Story
Data Analysis as a career
Do you know which the sexiest job of the 21st Century is? As per the Harvard Business Review, it is Data Scientist. Though, technically, Data Scientists are a few notches above Data Analysts, becoming a Data Analyst makes it easier for you to become a Data Scientist.
Picking a career is one of the most critical decisions that we need to take.
According to 614 Group Analysis, Fraud Rates in TAG Certified Channels Dropped from 1.68% to 1.41%, as Industry Adopted Higher Standards
The Trustworthy Accountability Group (TAG), an advertising industry initiative to fight criminal activity in the digital advertising supply chain, released the results of its 2019 benchmark fraud study.
(See a demo here.)
While working on a Twitter sentiment analysis project, I ran into the problem of needing to filter out all non-English tweets. (Asking the Twitter API for English-only tweets doesn’t seem to work, as it nonetheless returns tweets in Spanish, Portuguese, Dutch, Russian, and a couple other languages.
** Nuit Blanche is now on Twitter: @NuitBlog ** Studying the great convergence ! Degrees of Freedom Analysis of Unrolled Neural Networks by Morteza Mardani, Qingyun Sun, Vardan Papyan, Shreyas Vasanawala, John Pauly, David DonohoUnrolled neural networks emerged recently as an effective model for learning inverse maps appearing in image restoration tasks. However, their generalization risk (i.e.Read Full Story
Suppose you ask a bunch of users to rate a set of movies on a 0-100 scale. In classical factor analysis, you could then try to explain each movie and user in terms of a set of latent factors.Read Full Story
Google Analytics for Firebase is a powerful tool for mobile app development and data analysis. There are many reports that can help you measure the impact of your app on your business. In my previous blog, I listed down some…
The post Firebase Analytics: 4 Key Features that Product Managers can Leverage for Deeper Insights appeared first on Tatvic Analytics.
A year ago today, I wrote up a blog post Text analysis of Trump’s tweets confirms he writes only the (angrier) Android half.
My analysis, shown below, concludes that the Android and iPhone tweets are clearly from different people, posting during different times of day and using hashtags, links, and retweets in distinct ways.
“A lot of good analysis is wasted doing the wrong thing.”Anyone who has worked with data on business problems is probably aware of this adage. And this past week, I was reminded once again of this fact while analyzing a marketing program.Read Full Story
I’ll keep this short and sweet. I did an analysis of The Killers using some NLP techniques in my last blog post. I scraped both The Killers and Lana Del Rey lyrics previously for some topic model analysis, but it wasn’t so successful. To not waste my scraped data, here are the same results for Lana Del Rey. For details on methodology, you can go check that out.
When was the last time you ran a competitive analysis for your brand?
And most importantly, do you know how to do one efficiently?
If you’re not sure, or if the last “analysis” you ran was a quick perusal of a competitor’s website and social media presence, you’re likely missing out on important intelligence that could help your brand grow.
A different form of statistical analysis could prove benefitial, but I think the main thing to keep in mind is that data mining algorithms just show you what trends there are in the data, rather than prove anything concretely. If a trend is found in the data, that is the beginning rather than the end of the research.Read Full Story
We illustrate the application of two linear compression algorithms in python: Principal component analysis (PCA) and least-squares feature selection. Both can be used to compress a passed array, and they both work by stripping out redundant columns from the array.Read Full Story
Every survival analysis method I’ve talked about so far in this series has had one thing in common: we’ve only looked at one event in a customer lifetime (churn). In many cases, that’s a perfectly fine way to go about things… we want our customers to stick with us, so churn is the event of interest.Read Full Story
I’ve trained a sentiment analysis on simple data set:
Amazon Reviews: Unlocked Mobile Phones
based on the amazon phone purchase reviews. Simple linear SVM classifier using scikit-learn.
pandas is a powerful, open source Python library for data analysis, manipulation, and visualization. I’ve been teaching data scientists to use pandas since 2014, and in the years since, it has grown in popularity to an estimated 5 to 10 million users and become a “must-use” tool in the Python data science toolkit.
I started using pandas around version 0.14.
A post-hoc analysis, part 2
As I wrote in my last blog post, around 3 years ago I decided to try to build a budgeting service like mint.com for the norwegian market. After around a year, having reached the prototype stage, I decided to take a short break from further building, to think about the business details. This quickly turned into an … extended break.
This article is an extension of a previous one I wrote when I was experimenting sentiment analysis on twitter data. Back in the time, I explored a simple model: a two-layer feed-forward neural network trained on keras. The input tweets were represented as document vectors resulting from a weighted average of the embeddings of the words composing the tweet.Read Full Story