Author: Ekaba Bisong

On day one of the Google NEXT 2018 conference which has a sold-out attendance at San Francisco’s Moscone center, Google’s drive and mission for cloud dominance and on-boarding of enterprise clients couldn’t be more poignant. At this conference, Google Cloud…

Amazon SageMaker and Google Datalab have fully managed cloud Jupyter notebooks for designing and developing machine learning and deep learning models by leveraging serverless cloud engines. However, as much as they have in common, there are key differences between the…

Amazon SageMaker is another cloud-based fully managed data analytics/ machine learning modeling platform for designing, building and deploying data models. The key selling point of Amazon SageMaker is “zero-setup”. The concept of “zero-setup” means data science teams can entirely focus…

This post gives a systematic overview of the vital points to consider when building supervised learning models. We address in Q&A style some of the key decisions/issues to go over when building a machine learning/ deep learning model. Whether you…

Learning is a non-trivial task. How we learn deep representations as humans are high up there as one of the great enigmas of the world. What we consider trivial (and to some others natural) is a complex web of fine-grained…

Machine learning is a technology that has grown to prominence over the past ten years (as at this time of writing) and is fast paving the way for the “Age of Automation”. This post provides a holistic view of the…

In a previous post titled Machine Learning on the cloud, we examined in plain language what is machine learning, what is the cloud, and the merits of leveraging cloud resources for machine learning practice. In this post, we introduce the…

What is Machine Learning? Machine learning is an assortment of tools and techniques for predicting outcomes and classifying events, based on a set of interactions between variables (also referred to as features or attributes) belonging to a particular data set….