Towards Data Science

Aug 2, 2018 Photo by JESHOOTS.COM on Unsplash Look at this equation: Value function of Reinforcement Learning If it does not intimidate you, then you are a mathematical savvy and there … Read more

Recently I came across this cooking recipes data set in Kaggle, and it inspired me to combine 2 of my main interests in life. Food and machine learning. What makes … Read more

So you’ve seen the recent news about how artificial intelligence (AI) is changing everything. However, the idea of AI has been around for a long time. Machines that think and … Read more

Estimators were introduced in version 1.3 of the Tensorflow API, and are used to abstract and simplify training, evaluation and prediction. If you haven’t worked with Estimators before I suggest … Read more

Jul 19, 2018 Hypothesis analysis is a widely known concept and is used extensively by researchers, statisticians and quantitative analysts. It allows them to follow a set of formal steps … Read more

DIY Noise-Cancellation System prototype made with TensorFlow. Jun 25, 2018 Image by TheDigitalArtist on Pixabay In this post I describe how I built an active noise cancellation system by means of … Read more

Introduction Learning rate might be the most important hyper parameter in deep learning, as learning rate decides how much gradient to be back propagated. This in turn decides by how … Read more

I’ve been involved in building several different types of recommendation systems, and one thing I’ve noticed is that each use case is different from the next, as each aims to … Read more

Jun 14, 2018 This post is about implementing simple linear regression model for ML beginners in step by step way with detailed explanation. If you are new to machine learning, … Read more

Using MQTT protocol, we will get captured data from sensors, logging them to an IoT service, ThingSpeak.com and to a mobile App, Thingsview. 1. Introduction In my previous article, MicroPython … Read more

When you are using Google’s Colaboratory (Colab) for running your Deep Learning models the most obvious way to access the large datasets is by storing them on Google Drive and … Read more

Over the past few decades, four key change initiatives have been taking place in the organizations: strategic planning, re-engineering, total quality management and downsizing. The aim of these initiatives was … Read more

This post attempts to consolidate information on tree algorithms and their implementations in Scikit-learn and Spark. In particular, it was written to provide clarification on how feature importance is calculated. … Read more

Apr 15, 2018 In this post, we will tackle one of the most challenging yet interesting problems in Natural Language Processing, aka Question Answering. We will implement Google’s QANet in … Read more

On centralizing siloed data Apr 12, 2018 I still get nostalgic looking at the very first Pebbles. (Photo courtesy of Pebble’s first Kickstarter) In 2014, I joined Pebble, the smartwatch maker … Read more

Greg Lamp, previous co-founder of the data science startup Yhat, and current co-founder & CTO of Waldo shares his thoughts on Machine Learning for those of us who just don’t … Read more

Dissimilarity MatrixArguably, this is the backbone of your clustering. Dissimilarity matrix is a mathematical expression of how different, or distant, the points in a data set are from each other, … Read more

4. Course Content The content of each course is world-class. I’ve frequently stated in my videos these are the best courses I’ve ever taken. The DLND is broken into six … Read more

An analytics roadmap for growth Scenario — You’re an up-and-coming ecommerce/SaaS startup. You’ve got your site up, you have A/B tested your message, and you’ve got your SEO, and social … Read more

Feb 22, 2018 I do not hold ownership to any of the above pictures. These are merely used for educational purposes to describe the concepts. Real time multiple object localization … Read more

An overview and implementation in R Feb 19, 2018 Fig 1: Performance of an individual — Poor, Fair, Excellent Can you guess what is the common link in the variables mentioned below: Job … Read more

The idea behind using a Keras generator is to get batches of input and corresponding output on the fly during training process, e.g. reading in 100 images, getting corresponding 100 … Read more

It’s not enough to do data analysis (Credit rawpixel: Unsplash) Stop management from ignoring your analysis Feb 3, 2018 To a data analyst, there is nothing more exciting than the data … Read more

4) Under the hood: expressing computations TensorFlow could be considered a programming system and runtime, not just a “library” in the traditional sense: TensorFlow’s graph even supports constructs like variable … Read more

Jan 13, 2018 The computing world has seen increasing attention on microservices software architecture in order to enhance software scalability and efficiency. Microservices brings many benefits for tech organizations. However, … Read more

Reinforcement Learning (RL) is one of the most happening field of Machine Learning (ML) and Artificial Intelligence (AI).Though RL existed for many decades, only recently the giant has awaken after … Read more

Nov 27, 2017 By: Team Vesta, University of Southern California. CSCI:599 Deep Learning and Its Applications Suraj Jayakumar (sjayakum@usc.edu), Rakesh Ramesh (rakeshr@usc.edu), Pradeep Thalasta (thalasta@usc.edu) Introduction: The recent success of … Read more

Combining card games and topic modeling Nov 27, 2017 This article sparked an interesting discussion on reddit and was featured by Wizards of the Coast. One of the coolest projects I’ve … Read more

An overview and implementation in R Oct 31, 2017 Customer satisfaction for a product — Satisfied vs Dissatisfied (Source: pixabay.com) Have you ever come across a situation where you want to predict a … Read more

Oct 20, 2017 In the second of four informal discussion sessions, Professor Maurits Kaptein from Tilburg University discussed the methodological challenges of data science. ‘’Before discussing the biggest challenges we … Read more

Aug 15, 2017 Credits: Presenting abridged version of these blogs to explain the idea and concepts behind pix2pix and cycleGANs. Christopher Hesse blog: Olga Liakhovich blog: Pix2Pix: paper: https://phillipi.github.io/pix2pix/ pix2pix … Read more

I’ve said yes to far too many hidden units Part of the How I’m Learning Deep Learning Series: Part I: A new beginning.Part II: Learning Python on the fly.Part III: … Read more

While replicating the End-to-End Deep Learning approach for Self- Driving Cars, I was frustrated by the lack of visibility into what the network is seeing. I built a tool to … Read more

Implementing the Perceptron Perceptron is one the most elegant yet easy to implement learning algorithms. Though most packages/libraries provide implementation for this algorithm, let us try our hand on it … Read more

Aug 13, 2016 “From the barren landscapes inside our personal devices come furtive anthems hummed by those digital servants who will one day be our overlords” A.I. winter The idea … Read more

This will make your life easy. Thank me later Oct 8, 2015 Photo by Markus Spiske on Unsplash Shell Commands are powerful. And life would be like hell without shell is how … Read more