Unicorns, Reproducibility, and other Machine Learning Myths20190314101406
Unicorns, Reproducibility, and other Machine Learning Myths
March 14, 2019data science, enterprise, machine learning
“Everybody is a genius. But if you judge a fish by Its ability to climb a tree, it will live Its whole life believing that it is stupid.” While common...
How to do Machine Learning without Learning Data Science20181009154501
How to do Machine Learning without Learning Data Science
October 9, 2018data science, keras, machine learning, ml
For all that TensorFlow is the current darling of the Machine Learning (ML) crowd, it’s just a graphing library that represents a series of commands a...
Machine Learning – The New Cornerstone of Digital Transformation20180502172132
Machine Learning – The New Cornerstone of Digital Transformation
May 2, 2018activepython, ai, artificial intelligence, data science, machine learning, ml
Artificial Intelligence (AI), and more pragmatically, Machine Learning (ML) have been called the new electricity that’s powering the Fourth Indu...
Data is the foundation of your ML strategy20180412020008
Data is the foundation of your ML strategy
April 12, 2018data science, machine learning, ml
When getting started with machine learning (ML) you need data — and lots of it. Data really forms the foundation of your machine learning strate...
Python: Bridge between Data Science & Engineering, to reach Machine Learning20180320044343
Python: Bridge between Data Science & Engineering, to reach Machine Learning
March 20, 2018data science, engineering, machine learning, python
*Note: this post was originally posted on LinkedIn. We’re starting our own March madness, and it’s all about machine learning (ML). Want to share you...
Accelerating Your Algorithms: Considerations in Design, Algorithm Choice and Implementation20171102130109
Accelerating Your Algorithms: Considerations in Design, Algorithm Choice and Implementation
November 2, 2017activepython, algorithms, data science, optimization, python
The pursuit of speed is one of the few constants in computing, and it is driven by two things: ever-increasing amounts of data, and limited hardware r...
Using Pre-Trained Models with TensorFlow in Go20170818130748
Using Pre-Trained Models with TensorFlow in Go
August 18, 2017coco-stuff, common objects in context, data science, go, golang, image identification, machine learning, object identification, pre-trained tensorflow
One of the challenges with machine learning is figuring out how to deploy trained models into production environments. After training your model, you ...
Robust Algorithms for Machine Learning20170720141501
Robust Algorithms for Machine Learning
July 20, 2017activepython, data analysis, data science, jupyter notebook, keras, pandas, python, robust algorithms, scipy
Machine learning is often held out as a magical solution to hard problems that will absolve us mere humans from ever having to actually learn anything...
R vs Python: A False Dichotomy20160223170000
R vs Python: A False Dichotomy
February 23, 2016data science, python, r, Rpy, rpy2
There have been a few articles lately posing the age old question: “Is R or Python a better language to learn for a budding young data scientist?̶...