Background

Robotics today is not…

I’d like to introduce a series of blog posts and their corresponding Python Notebooks gathering notes on the Deep Learning Book from Ian…

In this…

Introduction

With the recent…

This book, initially written for chemical engineers, is actually very interesting for data scientists and machine learning engineers alike. For more free books,…

On Linkedin, many Data Science enthusiasts who aspire to be…

I built a scenario for a hybrid machine learning infrastructure leveraging Apache Kafka as scalable central nervous system. The public cloud is used for…

Summary: There are some interesting use cases where combining CNNs and RNN/LSTMs seems to make sense and a number of researchers pursuing this.  However, the latest…

In this post, I explore if ideas…

Andrew Ng is a great fan of reading research papers as a long…

This big picture view lays the foundation of our book Data Science for…

You may even call it post-doctorship, as the level is beyond the traditional PhD degree. It is not a degree, not competing with university programs, but instead, akin to a fellowship or…

One of most excruciating pain points during Data Exploration and Preparation stage of an Analytics project are missing values.

How do you deal with missing values - ignore…

I have a close circle of clued-on/tech savvy friends whose views I…

Background

Last week, I spoke at…

Last week, at an event on AI, I asked the panel about how investors evaluate the Data readiness of AI start-ups. This subject is close to my work and my teaching. I teach a course on…

It's a complete tutorial on data wrangling or manipulation with R. This tutorial covers one of the most powerful R package for data wrangling i.e. dplyr. This package was written by the most…

Introduction:

Background – How many cats does it take to identify a Cat?

In this article, I cover the 12 types of AI problems i.e. I address the question : in which…

Machine Learning is all about creating an artificial brain to perform a…