For a limited time only, we are offering to showcase 3 of our popular demos for FREE*. These one-hour amazing demos are great fun to watch and learn from. If you like us to conduct either in-person or over Zoom these demos for your organizations or teams, please fill up the form (see below) and then click the Request For Demo button.
Identify Donald Trump’s tweets with Naive Bayes
Donald John Trump, 45th president of the United States of America, is a prolific twitter with a following of more than 20 million. Could we use a simple machine learning algorithm to identify if a given tweet is from Donald Trump? Yes!
Attending Workshops From Home!
GOOD NEWS! You can now attend our workshops on-line! Beginning 2021, you can attend our workshops from wherever you may be – by the swimming pool or even at location overseas. Here’s more good news – the fees for on-line
Webinar – Wonders of Machine Learning!
BRAND NEW WEBINAR SERIES ON Machine Learning! Exclusively for the SMU Alumni & Staff! In collaboration with Singapore Management University (SMU), we are launching our brand new Zoom webinar series Wonders of Machine Learning on 4 September 2020 (Friday) from 5 to
First Step Towards Data Science
The First Step is to learn Python, an open-source simple and powerful language that is widely used in many domains, particularly in Data Science. Python has a huge repertoire of supporting libraries (a.k.a. frameworks) for all kinds of applications, including Machine Learning.
Determine the number of Iris species with k-Means
k-Means is a simple and popular unsupervised machine learning clustering algorithm, commonly used for market segmentation. The algorithm computes the distance squared between each data point and each cluster centroid. Then each data point is assigned to the nearest cluster.
Predictive Analytics using Multivariate Regression
Another awesome framework (a.k.a library) in Python is scikit-learn. The framework provides a simple and consistent API for data modeling and analytics. With scikit-learn, it is easy to implement key machine learning algorithms e.g. Multivariate Regression, Naives Bayes, Neural Network, … etc.