12 Key Lessons from ML researchers and practitioners
Machine learning algorithms come with the promise of being able to figure out how to perform important tasks by learning
Deep Learning Series, P3: Understanding Recurrent Neural Networks
1. Why RNNs? Your smartphone predicting your next word when you are typing, Alexa understanding what you are saying or
The data-driven coffee – analyzing Starbucks’ data strategy
We often go through life without pausing to think about the behind-the-scenes of events or things that are part of
Deep Learning Series, P2: Understanding Convolutional Neural Networks
Neural Networks come in many flavors and varieties. Convolutional Neural Networks (ConvNets or CNN) are one of the most well
Deep Learning Series, P1: Basics of Neural Networks and Understanding Gradient Descent
This post consists of the following two sections: Section 1: Basics of Neural Networks Section 2: Understanding Backward Propagation and
How great products are made: Rules of Machine Learning by Google, a Summary
Google recently published some nuggets of ML wisdom, i.e., their best practices in ML Engineering. I believe that everyone should
AI, Drones and Game Theory For Smart Wildlife Conservation
Background As the human population keeps booming, our actions are pushing life on our shared planet towards mass extinction. Human activity
Understanding Word Embeddings
How is Google Translate able to understand text and convert it from one language to another? How do you make
Time Series Forecasting, the easy way! Let’s analyze Microsoft’s stocks
Introduction Time series forecasting and understanding time based patterns have many important applications. However, it is a territory often left
Click-Through Rate (CTR) Prediction using Decision Trees
1. Introduction In this tutorial, we will try to predict click-through rate of ads with the Decision Tree algorithm we
