Moral Dilemmas of Self-Driving Cars

How Should Autonomous Machines Decide Who Not To Kill? I would love to have my own self-driving car. I mean, who wouldn’t? But they’re not perfect. If you think about it, self-driving cars have to make decisions like you and I. They don’t eliminate the possibility of collisions (yet)… just decrease the chances of it happening … Read moreMoral Dilemmas of Self-Driving Cars

Applications of Graph Neural Networks

Graphs and their study have received a lot of attention since ages due to their ability of representing the real world in a fashion that can be analysed objectively. Indeed, graphs can be used to represent a lot of useful, real world datasets such as social networks, web link data, molecular structures, geographical maps, etc. … Read moreApplications of Graph Neural Networks

Machine Thinking, Conveyance, and the Future of Design

The Swing In our rapidly-evolving digitally-centric world, I often fall into the trap of thinking of design as the latest glossy app or shiny consumer electronics product. It’s easy to lose sight of the fact that design is as old as human kind; an ancient and innate part of who we are as a species. … Read moreMachine Thinking, Conveyance, and the Future of Design

AirBnB listings in Seattle: A deeper look

Question 3: Variations amongst neighborhoods in Seattle 3.a Where are most listings concentrated There are two attributes provided in the dataset that indicate the location of the listing. One is neighborhood and the other is neighborhood group. The latter splits the city into 17 areas while the former splits the city into 87 areas. Here … Read moreAirBnB listings in Seattle: A deeper look

Regression: Kernel and Nearest Neighbor Approach

Nadaraya-Watson Kernel-Weighted Average Regression In the above method, one of the major drawbacks was the equal assignment of weights. This method assigns weights to each point in a window of query point based on a specific Kernel. Main intuition is that weights should decrease with increase in distance and more weights should be assigned for … Read moreRegression: Kernel and Nearest Neighbor Approach

Neural-Symbolic VQN — Disentagled Reasoning — Or — The answer: disentanglement

An explanation of an interpretable deep learning system. Nearly every technological step forward starts with an example from science fiction. So before I am going to explain what these scientists built, I want you to watch a part of an episode of the classic TV series Star Trek — Next Generation, The Identity Crisis. Play the embedded video from … Read moreNeural-Symbolic VQN — Disentagled Reasoning — Or — The answer: disentanglement

Data Analysis of 10.000 AI Startups

Extracting insights from AngelList companies Introduction AngelList is a place that connects startups to investors and job candidates looking to work at startups. Their goal is to democratize the investment process, helping startups with both fundraising and talent. Be it to find a job, investors for a startup, or even if just to make connections, … Read moreData Analysis of 10.000 AI Startups

Video Games as a Perfect Playground for Artificial Intelligence

Why video games are so good for machine learning? One of the first reasons behind the popularity of video games among AI researchers is the tendency of video games to mimic real life in many ways. This idea is not very straightforward when it comes to older games, as they have arcade-style graphics and physics. … Read moreVideo Games as a Perfect Playground for Artificial Intelligence

Simple guide for ensemble learning methods

What, why, how and Bagging-Boosting demystified, explained rather unconventionally, read on:) JuhiBlockedUnblockFollowFollowing Feb 25 Before this post, I have published a “Holy grail for Bias variance trade-off, Overfitting and Underfitting”. This comprehensive article serves as an important prequel to this post if you are a newbie or would just like to brush up the concepts of … Read moreSimple guide for ensemble learning methods

Why Doing Good Science is Hard and How to Do it Better

Photo by Steve Johnson on Unsplash Doing good science is hard and a lot of experiments fail. Although the scientific method helps to reduce uncertainty and lead to discoveries, its path is full of potholes. In this post, you’ll learn about common p-value misinterpretations, p-hacking, and the problem with performing multiple hypothesis tests. Of course, not … Read moreWhy Doing Good Science is Hard and How to Do it Better

Rating Sports Teams — Elo vs. Win-Loss

Photo by Ariel Besagar on Unsplash Which is better? Introduction There are many ways to determine who is the best team or player in any sport. You can look at the last 5 games. The last 10 games. You can use score differential. You can rate them on which teams “feel” the best. You can look at … Read moreRating Sports Teams — Elo vs. Win-Loss

Understand how your TensorFlow Model is Making Predictions

Introduction Machine learning can answer questions more quickly and accurately than ever before. As machine learning is used in more mission-critical applications, it is increasingly important to understand how these predictions are derived. In this blog post, we’ll build a neural network model using the Keras API from TensorFlow, an open-source machine learning framework. One … Read moreUnderstand how your TensorFlow Model is Making Predictions

Build Your First Open Source Python Project

A step-by-step guide to a working package Every software developer and data scientist should go through the exercise of making a package. You’ll learn so much along the way. Making an open source Python package may sound daunting, but you don’t need to be a grizzled veteran. You also don’t need an elaborate product idea. You … Read moreBuild Your First Open Source Python Project

Remote Sensing Basics: Normalized Difference Vegetation Index

Applications of Satellite Imagery for Ecology Research NDVI visualization of continental US If you haven’t already, please check out my previous post that summarizes my capstone project from General Assembly’s Data Science Immersive course: Land-use and Deforestation in the Brazilian Amazon. It is a good introduction to some of my interests in machine learning, remote sensing, … Read moreRemote Sensing Basics: Normalized Difference Vegetation Index

Get started with Apache Spark and TensorFlow on Azure Databricks

TensorFlow is now available on Apache Spark framework, but how do you get started? It called TensorFrame TL;DR This is a step by step tutorial on how to get new Spark TensorFrame library running on Azure Databricks. Big Data is a huge topic that consists of many domains and expertise. All the way from DevOps, … Read moreGet started with Apache Spark and TensorFlow on Azure Databricks

An Exercise on Basic R: How’s Kickstarter Doing These Days?

Basic Data Manipulation and Visualization with tidyverse and ggplot2, published with mediumR It’s a practice story! I didn’t realize the tables/tibbles would be poorly shaped after importing from R directly to Medium. If anyone has ever faced this, please drop a link for me to refer to! I got my hands on 2018 January Kickstarter data-set from … Read moreAn Exercise on Basic R: How’s Kickstarter Doing These Days?

State of Data Science & Machine Learning

Data Scientist Arsenal Data science and Machine Learning technology landscape are ever expanding. It is not humanly possible to be expert in all the available frameworks, platforms and methodologies. The survey has captured Programming Languages, Frameworks, Tools & Platforms that are used and suggested by the participants. Ignoring the edge cases, this should give a … Read moreState of Data Science & Machine Learning

From archaeology to data science: the joy of iterative career paths

Discovering my love of all things data At school I hadn’t planned on doing anything particularly technical as a career. I took a maths A-level largely as a refreshing break from the essay-writing of history and English lit, and the time-consuming creativity of fine art. I went to Cambridge to study Archaeology and Anthropology (another iterative … Read moreFrom archaeology to data science: the joy of iterative career paths

Why and how global brands like Facebook and Danone invest in market research

Last week, I received the following email from Facebook: “Hi Joei, Facebook is seeking candid feedback from individuals who create online videos on Facebook, Instagram and other platforms. Please help us do that by taking a simple survey here…” Thanks, The Facebook Research Team” This made me think: if Facebook, one of the world’s fastest-growing … Read moreWhy and how global brands like Facebook and Danone invest in market research

AI Gets Creative Thanks To GANs Innovations

For an Artificial Intelligence (AI) professional, or data scientist, the barrage of AI-marketing can evoke very different feelings than for a general audience. For one thing, the AI industry is incredibly broad and has many different forms and functions, so industry professionals tend to focus more deeply on which branches of AI are being hyped … Read moreAI Gets Creative Thanks To GANs Innovations

Python, Oracle ADWC and Machine Learning

How to use Open Source tools to analyze data managed through Oracle Autonomous Data Warehouse Cloud (ADWC). Introduction Oracle Autonomous Database is the latest, modern evolution of Oracle Database technology. A technology to help managing and analyzing large volumes of data in the Cloud easier, faster and more powerful. ADWC is the specialization of this technology … Read morePython, Oracle ADWC and Machine Learning

A beginner’s guide to Linear Regression in Python with Scikit-Learn

Simple Linear Regression Linear Regression While exploring the Aerial Bombing Operations of World War Two dataset and recalling that the D-Day landings were nearly postponed due to poor weather, I downloaded these weather reports from the period to compare with missions in the bombing operations dataset. You can download the dataset from here. The dataset … Read moreA beginner’s guide to Linear Regression in Python with Scikit-Learn

Deploy ML/DL Models to Production via Panini

What is Panini? Panini is a platform that serves ML/DL models at low latency and makes the ML model deployment to production from a few days to a few minutes. Once deployed in Panini’s server, it will provide you with an API key to infer the model. Panini query engine is developed in C++, which provides … Read moreDeploy ML/DL Models to Production via Panini

Deep Active Noise Cancellation

RNN predicts a structured noise to suppress it in a complex acoustic environment Flickr, CC BY-NC 2.0 In my previous post I told about my Active Noise Cancellation system based on neural network. Here I outline my experiments with sound prediction with recursive neural networks I made to improve my denoiser. The noise sound prediction … Read moreDeep Active Noise Cancellation

Cryptocurrency Analysis with Python — MACD

I’ve decided to spend the weekend learning about cryptocurrency analysis. I’ve hacked together the code to download daily Bitcoin prices and apply a simple trading strategy to it. Note that there already exists tools for performing this kind of analysis, eg. tradeview, but this way enables more in-depth analysis. Disclaimer I am not a trader … Read moreCryptocurrency Analysis with Python — MACD

Tips & Tricks in Multiple Linear Regression

Gathered methods to analyse data, diagnose models and visualize results This analysis was a project which I decided to undertake for the Regression Analysis module in school. I have learnt and gathered several methods you can use in R to take your depth of analysis further. As usual, I always learn the most discovering on … Read moreTips & Tricks in Multiple Linear Regression

Convolutional Neural Network

Learn Convolutional Neural Network from basic and its implementation in Keras Table of contents What is CNN ? Why should we use CNN ? Few Definitions Layers in CNN Keras Implementation 1. What is CNN ? Computer vision is evolving rapidly day-by-day. Its one of the reason is deep learning. When we talk about computer vision, a term convolutional neural … Read moreConvolutional Neural Network

Sentiment Analysis with Deep Learning

Recognize and Classify Human Emotions in Netflix Reviews In this article, I will cover the topic of Sentiment Analysis and how to implement a Deep Learning model that can recognize and classify human emotions in Netflix reviews. One of the most important elements for businesses is being in touch with its customer base. It is vital … Read moreSentiment Analysis with Deep Learning

Data Pre-processing with Pandas on Trending YouTuBe Video Statistics 〠 ❤︎ ✔︎

The purpose of this article is to provide a standardized data pre-processing solution that could be applied to any types of datasets. You will learn how to convert data from initial raw form to another format, in order to prepare the data for exploratory analysis and machine learning models. Overview of the data This dataset is … Read moreData Pre-processing with Pandas on Trending YouTuBe Video Statistics 〠 ❤︎ ✔︎

Data Science for Fitness: 50 is the new 30 — Part I

The following article will try to explain a very interesting experience for me, that along with the algorithmic music composition algos (sans neural nets) I developed in 2013–2014 is one of the most rewarding projects I have undertaken: Data Science for Fitness. In these series of practical applications of Data Science (aren’t you tired of … Read moreData Science for Fitness: 50 is the new 30 — Part I

Job Satisfaction and success in the How How to succeed in the coding world

A data driven approach: Success Mantras Using Stack overflow Survey Data from 2017 Introduction Success may have different meaning for different people. So, what does it take to become a successful developer? The short answer would be it varies from person to person. Success in this articles’ context though implies job satisfaction and higher salary. There … Read moreJob Satisfaction and success in the How How to succeed in the coding world

Will Artificial Intelligence take shortcuts? or is it just us?

We all think alike, no one thinks very much — Walter Lippmann The information age is overflowing with information and choices. What is the best car to buy, what is the best course to take, what is the best pressure cooker brand to purchase. In the face of these choices, the most logical yet almost impossible thing … Read moreWill Artificial Intelligence take shortcuts? or is it just us?

Deep learning based super resolution, without using a GAN

This article describes the techniques and training a deep learning model for image improvement, image restoration, inpainting and super resolution. This utilises many techniques taught in the Fastai course and makes use of the Fastai software library. This method of training a model is based upon methods and research by very talented AI researchers, I’ve … Read moreDeep learning based super resolution, without using a GAN

Preparing for a Machine Learning Interview — Introduction

Deep Learning Photo by Ian Stauffer on Unsplash The deep learning part of the interview stack is mostly focused on finding out whether you have gotten your hands dirty. The questions tend to be around engineering challenges that a deep learning engineer faces on an everyday basis. The interviewer is trying to gauge whether or not … Read morePreparing for a Machine Learning Interview — Introduction

XY Universe: A 2D Particle Survival Environment for Deep Reinforcement Learning

We provide here XY Universe: a 2D particle survival environment for training your Deep Reinforcement Learning agents to stay alive as long as possible by avoiding collisions with “bad” particles. The agent and the “bad” particles are confined to a 2D box, move with fixed constant speed, and experience elastic collisions against the box walls. … Read moreXY Universe: A 2D Particle Survival Environment for Deep Reinforcement Learning

Utilizing Convolutional Neural Networks (CNNs) for Predicting DNA-Protein Interactions and…

Over the last few years, the exponential progress in the fields of machine and deep learning have a spun a new way to solve some of healthcare’s most plaguing problems: deep learning. In fact, the market for AI in healthcare is estimated to top $36 billion by 2025! From diagnosing patients for various forms of … Read moreUtilizing Convolutional Neural Networks (CNNs) for Predicting DNA-Protein Interactions and…

Creating Bots That Talk Like Humans With Natural Language Processing

An accurate response to one of the First-World’s most annoying problems. We’ve all been there: You want to change your cell phone plan, or figure out why your damn TV isn’t working (seriously, this is way too complicated sometimes), so you go ahead and dial customer service. As you put the phone to your ear, … Read moreCreating Bots That Talk Like Humans With Natural Language Processing

Your Unpredictable Daily Schedule Might Be Wrecking Your Estimates

I only have data about myself, of course, but I’m very curious about other developers. Are there developers with little variance, and each day they work on their main project consistently close to some average? Until I started collecting data, I thought I was one of those developers. But it turns out, I am not. … Read moreYour Unpredictable Daily Schedule Might Be Wrecking Your Estimates

How to Practice Python with Google Colab?

Automatic setting-up, getting help effectively, collaborative programming, and version control. A one-stop solution to the pain points in Python beginners’ practice. Pain Points This semester, I started to teach the course “INFO 5731: Computational Methods for Information Systems” at University of North Texas (UNT), which includes the foundation of Python, Natural Language Processing and Machine … Read moreHow to Practice Python with Google Colab?

The Complete Reinforcement Learning Dictionary

The Dictionary Action-Value Function: See Q-Value. Actions: Actions are the Agent’s methods which allow it to interact and change its environment, and thus transfer between states. Every action performed by the Agent yields a reward from the environment. The decision of which action to choose is made by the policy. Actor-Critic: When attempting to solve … Read moreThe Complete Reinforcement Learning Dictionary

All you need to know about text preprocessing for NLP and Machine Learning

Based on some recent conversations, I realized that text preprocessing is a severely overlooked topic. A few people I spoke to mentioned inconsistent results from their NLP applications only to realize that they were not preprocessing their text or were using the wrong kind of text preprocessing for their project. With that in mind, I … Read moreAll you need to know about text preprocessing for NLP and Machine Learning

Nature’s Patterns are Changing: Explore 32 Years of Community Science Data

As a start to this small community based science experiment, I provide access to Latimer’s data and initial exemplar R code. This is by no means exhaustive, as the intent is to introduce the data scientists to the environmental data and, in turn, introduce the community scientists to some basic analytics in R. The hope … Read moreNature’s Patterns are Changing: Explore 32 Years of Community Science Data