5 YouTube Recommendations

It's been a while since my last blogpost here so I wanted to hop on here to share some updates. Lately I have been exploring video form of content creation because it allows me to connect better with you all. If you are following this blog, chances are that you will enjoy and benefit from...

Your Complete Guide to AI Career Pathways

So much confusion, so many doubts and questions around careers in AI! When deciding a career pathway, the lack of clarity can be really stressful. Instead of continuing to answer individual questions, I decided to address them once and for all. Developing an AI project involves various technical roles and tasks. Let's demystify them! In...

AI Index Report 2019: Major Takeaways (Summary)

Introduction As we enter 2020, the Stanford Institute for Human-Centered Artificial Intelligence has published its Artificial Intelligence Index - 2019 Report. The AI Index originated as part of a century-long Stanford study of AI’s progress and impact. The AI Index report examines in a very detailed manner the biggest trends shaping the AI industry, breakthrough research,...

BERT Explained: A Complete Guide with Theory and Tutorial

Unless you have been out of touch with the Deep Learning world, chances are that you have heard about BERT —  it has been the talk of the town for the last one year. At the end of 2018 researchers at Google AI Language open-sourced a new technique for Natural Language Processing (NLP) called BERT...

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 from data, i.e., generalizing from examples without being explicitly told what to do. This means that the higher the amount of data, the more ambtious problems can be tackled by these algorithms. However, developing successful machine...

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 tasks like making stock market predictions, understanding movie plots, composing music, language translation and human learning: can you tell what is the common theme in this list? These are examples where sequence of information is crucial.For...

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 known and important types of Neural Networks. They are mainly used in the context of Computer Vision tasks like smart tagging of your pictures, turning your old black and white family photos into colored images...

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 Gradient Descent Section 1 Introduction For decades researchers have been trying to deconstruct the inner workings of our incredible and fascinating brains, hoping to learn to infuse a brain-like intelligence into machines. For example, when...

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 know about such best practices, so let's look at them. Please read the following statement a couple of times before moving on: Do machine learning like the great engineer you are, not like the great...

Understanding Word Embeddings

How is Google Translate able to understand text and convert it from one language to another? How do you make a computer understand that in the context of IT Apple is a company and not a fruit? Or how is a Smart-Keypad able to predict the most likely next few words that you are going...