Big Data Roadmap – A roadmap for success with big data
I'm regularly asked about how to get started with big data. My response is always the same: I give them my big data roadmap for success.
Local Interpretable Model-agnostic Explanations – LIME in Python
Using LIME (Local Interpretable Model-agnostic Explanations) in Python to provide visual explanations of your classification and regression models.
Agile Marketing Based on Analytical Data Insights: Improving Scrum Tactics in Brand Outreach
Mathias Lanni highlights how to improve Scrum Marketing Management using smart data collection for better brand outreach.
Are your machine learning models good enough?
Guidance for non-technical people on how to ask the right questions to evaluate whether a machine learning model is good enough for the job.
Forecasting Time Series data with Prophet – Part 4
This is the fourth in a series of posts about using Forecasting Time Series data with Prophet. The other parts can be found here: Forecasting Time Series
2017: A year in review (and a preview of 2018)
A brief look back at 2017 and a quick preview of what 2018 looks like for me.
Deep learning – when should it be used?
When should deep learning be used? the answer isn't a simple one. The answer depends on the problem, data size and number of other factors.
When it comes to big data, think these three words: analyze; contextualize; internalize
Stop thinking about big data technologies. Think of ways to 'analyze, contextualize, internalize' your data instead.
Data and Culture go hand in hand
Data and culture must go hand in hand in modern organizations.
11 years, 1400 blog posts...and a pretty graph
As part of a tutorial on Text Analytics and Visualization I just finished over on technical blog called Python Data (where I blog about using python for
Text Analytics and Visualization
Using basic Text Analytics and Visualization techniques, keywords can be automatically extracted from text and relationships can be visualized.
The Data Way
When working with data, don't just find the answers to your questions. Keep digging and find new questions to ask.
Be pragmatic, not dogmatic
Rather than blindly follow your a 'successful' company, find ways to incorporate their successes into your organization. Be pragmatic, not dogmatic.
Text Analytics with Python – A book review
Text Analytics with Python by Dipanjan Sarkar provides an overview of how to use Python to perform text analytics / natural language processing.
Python and AWS Lambda – A match made in heaven
Using Python and AWS Lambda, I've been able to offload a number of python scripts (set up as API endpoints on AWS) to allow more flexibility and save money.
Get my thinking in your inbox — one idea per issue, no spam.
Three a week: the Tuesday newsletter, Foto Friday, and Sunday’s Weekly Intel. No spam. Unsubscribe anytime.