Can Machines Think?

A 2 min summary of the Turing Test and why it works Created by Katerina Limpitsouni How can we ascertain that machines can think? In Computing Machinery and Intelligence, 20th-century Computer Scientist Alan Turing argues that The Imitation Game, a thought experiment, is sufficient to determine a machine’s thinking ability. The Imitation Game is played … Read more Can Machines Think?

A python flask app that predicts the personality type on the basis of user entries using text…

The painting above (called vertical flow) by Irene Rice Perreria is one that I find most interesting. To me, it describes the heterogeneity in colors and also simultaneously how these different colors originate from the same essence. Colors at the end of the day operate on a spectrum rather than as individual points. One could … Read more A python flask app that predicts the personality type on the basis of user entries using text…

Why Betting on the Lottery is a Pretty Bad Idea (if you actually wish to win)

We’ve heard time and time again that it’s hard to win the lottery. But yet we still play it. Doesn’t a chance of 1 in 13,983,816* to hit the jackpot sound close to impossible and daunting? Apparently not. Or that 435,461/998,844* of the time you end up with 0 matching numbers and don’t earn anything? … Read more Why Betting on the Lottery is a Pretty Bad Idea (if you actually wish to win)

How AI and ML Support Cognitive Collaboration

The five phases of assisted AI Image Source: Pixabay.com Artificial Intelligence and Machine Learning are becoming catch-all terms that cover a wide swath of computing capacity and potential, and they are sometimes incorrectly used as labels to describe other technological advances such as graphics processing unit (GPU) power. For the purposes of this piece, I … Read more How AI and ML Support Cognitive Collaboration

The 8 Minute Guide To How Your Business Can Solve Problems with AI and Machine Learning

If you have known categories of something, machine learning can sort things into those categories. This is called classification. You can categorize visitors to your website into buckets based on their click patterns, gaining insights to what they are likely to buy or be interested in. Given some data about a person, a machine learning … Read more The 8 Minute Guide To How Your Business Can Solve Problems with AI and Machine Learning

My first small project in Python for browsing Reddit in office safely (Part 2)

Newly added features: 1. lcop (Leave comment on a post) param: submission_id lcop allows you to leave a comment to a submission. All you need to provide is the submission id of the post. Since login is required for leaving a comment, before proceeding any action, an automatic check of whether a user is logged … Read more My first small project in Python for browsing Reddit in office safely (Part 2)

Initializing neural networks

And that doesn’t work as well. While the idea was right, choosing a wrong factor can lead to diminishing gradients (values reaching 0). Choosing the right scaling factor — Xavier init What should the value of the scaling factor be? The answer is (1 /⎷input). This initialization technique is known as Xavier initialization. If you … Read more Initializing neural networks

Get Hand-drawn Visualization shaped Data for Teaching and Experimenting

drawdata.xyz The need for custom/fake data that follows a specific pattern / shape / distribution for experimenting and Teaching isn’t something new. Recently I had written about {fakir} which is an R package for generating fake data. Taking it one further step ahead, What-if, you could **draw** a visualization and download data for that particular … Read more Get Hand-drawn Visualization shaped Data for Teaching and Experimenting

NBA playoff win chances via Bayesian inference

diagnostic plots of samples from the posterior via the BayesFactor package BayesFactorAnother adaptation of Bayesian probability to traditional hypothesis testing applications comes in the form of so-called “Bayes Factors”. Put simply, a Bayes Factor is just a ratio of the likelihood of two hypotheses being true, in light of some data (also known as the … Read more NBA playoff win chances via Bayesian inference

How to start a writing carrier on Medium

Practical advice analysing the first month of a Towards Data Science writer Photo by Free-Photos on Pixabay One month ago I started writing stories on Medium. As an Artificial Intelligence enthusiast, I sent my blog posts to a publication called Towards Data Science (TDS) which has about 280k followers at the moment. This story is … Read more How to start a writing carrier on Medium

Generating Synthetic Images from textual description using GANs

Automatic synthesis of realistic images is extremely difficult task and even the state-of-the-art AI/ML algorithm suffer to fulfil this expectation. In this story I will talk about how to generate realistic images from textual description which describes the image. If you are a fan of Generative Adversarial Network [GAN] then you are at the right … Read more Generating Synthetic Images from textual description using GANs

Data Visualization: A Catalyst to Human Cognition

A symphony of concepts for understanding how foundations of visualization and narrative visualization aide in pattern recognition and decision-making image: https://www.nature.com/articles/d41586-018-02174-z Data visualizations have been around from the beginning of time. From the drawings on caves depicting a primitive way of life, to Charles Minard’s infographic about Napoleon’s March, visualizations have been used to communicate … Read more Data Visualization: A Catalyst to Human Cognition

Top Python Libraries: Numpy & Pandas

In this tutorial, I’ll try to make a brief description about two of the most important libraries in Python Numpy and Pandas. Without further delay lets go through Numpy first. Numpy numpy is the core library for scientific computing in Python. It provides a high-performance multidimensional array object and tools for working with these arrays. … Read more Top Python Libraries: Numpy & Pandas

RcppEigen 0.3.3.7.0

[This article was first published on Thinking inside the box , and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don’t. A new minor release 0.3.3.7.0 of RcppEigen arrived on … Read more RcppEigen 0.3.3.7.0

Going Serverless with OpenFaaS and Golang — The Ultimate Setup and Workflow

Note: This was originally posted at martinheinz.dev Serverless applications have been cool and hype for a while now and some interesting and useful platforms/tools/frameworks are emerging now. One of them is OpenFaaS which is open source Function as a Service tool for developing cloud-native serverless applications. In this blog post, I want to show you … Read more Going Serverless with OpenFaaS and Golang — The Ultimate Setup and Workflow

Kalman Filter(3) — Localisation in Continuous State Space

Apply Gaussian Distribution to Continuous State Space In past sessions, we tried to do localisation in a grid world, where our robot has different probabilities locating in different cells. In a word, the state space is discrete. To generalise the problem setting to continuous state space, we will get to the core of kalman filter. … Read more Kalman Filter(3) — Localisation in Continuous State Space

Another Self-Driving Car Accident, Another AI Development Lesson

So should self-driving car accidents stop us from developing the technology? Of course not! The technology has huge potential in saving a lot of lives. The AI might be biased or not sophisticated enough, but it has one treat that humans don’t. They never become emotional, or reckless, or sleepy. Done right, it should out-perform … Read more Another Self-Driving Car Accident, Another AI Development Lesson

Cloud Platforms: Changing Face of Advertising and Marketing

Real-time reporting, data analytics, and Management Administration Image Source: Pexels The market for marketing and advertising technology has seen a great deal of innovation over the past ten years — so much so that it now boasts well over 1,000 vendors, which has been organized into more than 75 categories. I believe this structure is … Read more Cloud Platforms: Changing Face of Advertising and Marketing

Glimpse into Spark 3.0 [Early Access]

Tushar Kapoor: (https://www.tusharck.com/) Apache continues to maintain a strong position by showcasing its preview release of Spark 3.0 for Big Data Science. According to the preview, Spark is coming with several big and important features. You can download the preview release form this link: https://archive.apache.org/dist/spark/spark-3.0.0-preview/ Let’s see some of its major features which invigorate its … Read more Glimpse into Spark 3.0 [Early Access]

But Where Does the Pickle Go?

Lesson 5 of “Practical Deep Learning for Coders” by fast.ai I’m working through the “Practical Deep Learning for Coders” course by fast.ai, and blogging about my experience. Since the incredibly generous fast.ai community has already made detailed notes for each lesson (see the ones for Lesson 5 here), I’m just writing about the parts of … Read more But Where Does the Pickle Go?

Easy Text-to-Speech with Python

Text to Speech Source: thenextweb.com Text-to-speech (TTS) technology reads aloud digital text. It can take words on computers, smartphones, tablets and convert them into audio. Also, all kinds of text files can be read aloud, including Word, pages document, online web pages can be read aloud. TTS can help kids who struggle with reading. Many … Read more Easy Text-to-Speech with Python

Building a Deep Image Search Engine using tf.Keras

Imagine having a data collection of hundreds of thousands to millions of images without any metadata describing the content of each image. How can we build a system that is able to find a sub-set of those images that best answer a user’s search query?What we will basically need is a search engine that is … Read more Building a Deep Image Search Engine using tf.Keras

Analysing Honeypot Data using Kibana and Elasticsearch

Let’s open up the honeypot! 🍯 As the deployed system has been running for a while now, I wanted to look at the attacks that have happened and also investigate some of the malicious threat actors. As the data is in Elasticsearch and viewable via Kibana, we won’t have to be grepping any log files … Read more Analysing Honeypot Data using Kibana and Elasticsearch

My R Style Guide

Notation and naming File names File names end in .R and are meaningful about their content: Good: string-algorithms.R utility-functions.R Bad: foo.R foo.Rcode stuff.R Function names Preferrably function names consist of lowercase words separated by an underscore. Using dot (.) separator is avoided as this confuses with the use of generic (S3) functions. It also prevents … Read more My R Style Guide

Practical Data Science with R, 2nd Edition, IS OUT!!!!!!!

[This article was first published on R – Win-Vector Blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don’t. Practical Data Science with R, 2nd Edition author Dr. Nina … Read more Practical Data Science with R, 2nd Edition, IS OUT!!!!!!!

Are Complex Algorithms Fair?

Image can be found at: https://www.law.com/legaltechnews/2019/08/06/risky-business-should-governments-be-reviewing-tech-companies-algorithms/?slreturn=20190719210403 How will Artificial Intelligence transform our society and what are the costs? We are in the early stages of a Fourth Industrial Revolution, as presidential candidate Andrew Yang has acknowledged. This inquiry has arisen through nostalgic language about the old manufacturing economy and questions about the fairness of complex … Read more Are Complex Algorithms Fair?

AWS Managed Services (AMS) now supports SUSE Linux Enterprise Server 12 SP4

AMS support of SUSE Linux Enterprise Server 12 SP4 coupled with Amazon EC2 High Memory Instances with up to 24 TB of memory, provides you with a managed infrastructure offering to run large in-memory databases like SAP Hana in their AMS managed landing zones. AMS support for SUSE Linux Enterprise Server 12 SP4 is available … Read more AWS Managed Services (AMS) now supports SUSE Linux Enterprise Server 12 SP4

Amazon DynamoDB adaptive capacity now handles imbalanced workloads better by isolating frequently accessed items automatically

Amazon DynamoDB adaptive capacity now handles imbalanced workloads better by isolating frequently accessed items automatically. If your application drives disproportionately high traffic to one or more items, DynamoDB will rebalance your partitions such that frequently accessed items do not reside on the same partition. This latest enhancement helps you maintain uninterrupted performance for your workloads. … Read more Amazon DynamoDB adaptive capacity now handles imbalanced workloads better by isolating frequently accessed items automatically

Elastic Fabric Adapter is now compatible with Intel® MPI Library

EFA is a network interface for Amazon EC2 instances that enables customers to run applications requiring high levels of inter-node communications at scale on AWS. With EFA, High Performance Computing (HPC) applications using the Message Passing Interface (MPI) and Machine Learning (ML) applications using NVIDIA Collective Communications Library (NCCL) can scale to thousands of CPUs … Read more Elastic Fabric Adapter is now compatible with Intel® MPI Library

Leave manual cluster resizing behind with Cloud Dataproc’s autoscalingLeave manual cluster resizing behind with Cloud Dataproc’s autoscalingSoftware Engineer for Cloud Dataproc

Building real-time, interactive data products with open source data and analytics processing technology is not a trivial task. It involves constantly balancing cluster costs with service-level agreements (SLAs). Whether you are using Apache Hadoop and Spark to build a customer-facing web application or a real-time interactive dashboard for your product team, it’s extremely difficult to … Read more Leave manual cluster resizing behind with Cloud Dataproc’s autoscalingLeave manual cluster resizing behind with Cloud Dataproc’s autoscalingSoftware Engineer for Cloud Dataproc

The Data-Driven Operating Model

Data and particularly machine learning are often thought of as silver bullets that can solve every business challenge. Subsequently, many businesses have or are in the process of building the necessary infrastructure and talent to deliver on the lofty promises that they believe data and machine learning can provide. This is the right move — … Read more The Data-Driven Operating Model

Lidar and Autonomous Driving Dataset

Lidar is not new technology.I read little bit content on lidar when I was studying GIS in 2015.I always interested in Terrains and Maps. Image from https://www.independent.co.uk/ What is Lidar? Lidar is a surveying method that measures distance to a target by illuminating the target with laser light and measuring the reflected light with a … Read more Lidar and Autonomous Driving Dataset

Neural Network tutorial with Devanagari Characters using PyTorch

We will be using PyTorch library to build our Neural Network. I wrote a small program plot_images for displaying the characters along with its labels. Let’s see what do we have in our CSV file df.head() will give us the top 5 columns of our data-frame, in our dataset, we have pixel values from 0 … Read more Neural Network tutorial with Devanagari Characters using PyTorch

How To Use Jupyter on Your Deep Learning Rig Remotely With SSH

I decided to go with RedHat for my Linux distribution to run my SSH server on. RedHat is very proven, and holds its own as one of the most commonly run server distributions. Honestly though, if you’re new to Linux, distro doesn’t really matter as Linux is overall pretty consistent across the board. I’m not … Read more How To Use Jupyter on Your Deep Learning Rig Remotely With SSH

“Sunlight is the best data disinfectant”

I’m sharing the second expert anecdote from my book, Human-in-the-Loop Machine Learning. I have been fortunate to chat with many leaders in the machine learning community about their experience. Many shared personal anecdotes with me that deserve a bigger audience. For each leader that is featured in the book there were two selection criteria: Their … Read more “Sunlight is the best data disinfectant”

Introducing Batch on GKE—modernizing HPC with Kubernetes in the cloudIntroducing Batch on GKE—modernizing HPC with Kubernetes in the cloudEngineering ManagerProduct Manager, Compute Engine

To install and get started with Batch on GKE, you can view the product documentation and visit the Batch on GKE page. As you explore Batch on GKE, we’d love to hear your feedback and feature requests – email us. Meeting you where you are with partnersBatch on GKE is a great solution for modernizing … Read more Introducing Batch on GKE—modernizing HPC with Kubernetes in the cloudIntroducing Batch on GKE—modernizing HPC with Kubernetes in the cloudEngineering ManagerProduct Manager, Compute Engine

Machine Learning and Data Analysis — Inha University (Part-4)

In this part of the series Machine learning and Data analysis offer by Inha University, Rep. of Korea I’ll try to narrate Built-in and User-defined Functions and Modules in Python. From my point of view, it’ll be helpful for the new learners in python to understand it clearly. If you like to start from the … Read more Machine Learning and Data Analysis — Inha University (Part-4)

Leading a Data Science Team when you are not a Data Scientist

This was me when I took a position managing a data science team. My background is in social science and policy. I never coded before outside of some Stata for my masters degree (and the use of “coding” in Stata is arguable) and most of my math and statistics ware based on social science research. … Read more Leading a Data Science Team when you are not a Data Scientist