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
Docker is a tool which helps developers build and ship high quality applications, faster, anywhere. Source Why Docker With Docker, developers can build any app in any language using any … Read more
Jul 8, 2018 In this tutorial we will discuss about integrating PySpark and XGBoost using a standard machine learing pipeline. We will use data from the Titanic: Machine learning from … Read more
In the previous post I covered the basics you need to know to work with SQL Server. In this post, I want to show you some more advanced techniques that … 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
After getting scrum.org the PSM I I wanted to capture the relevant content. The complete guido can be downloaded here: scrumguides.org 1. What is Scrum? Scrum is a framework for … 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
Many data professionals are strict on the language to be used for ANN models limiting their dev. environment exclusively to Python. I decided to test performance of Python vs. R … 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
Since R is mostly a functional language and data science work lends itself to be expressed in a functional form you can come by just fine without learning about object-oriented … 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
Measuring the effect of an intervention on some metric is an important problem in many areas of business and academia. Imagine, you want to know the effect of a recently … Read more
One of the things I particularly like about working in data science, is the science part: Figuring out the right questions to ask, how to frame a problem correctly and … Read more
data.table is an awesome R package, but there are a few things you need to watch out for when using it. R usually does not modify objects in place (e.g. by … Read more
When you work for a large corporation you often have little choice in picking a specific operating system for your company laptop. This post is a collection of random problems … 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
Here is a great tutorial on how to host hugo on netlify Other examples using the exact same theme: Creating the hugo site In order to create a new hugo … Read more
SQL is not the sexiest language on the block and many/most data scientists I know prefer to stick to R and/or Python. Some common complains I hear about SQL are: … Read more
Creating an R package is as easy as typing: package.skeleton(name = “YourPackageName”) As you might have guessed, this function creates the basic file and folder structure you need to create … Read more
Many data scientists are former academics who are used to working on a specific and often quite narrow research problems for long periods of time, often years. With data science … 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
I am an absolute fan of adapting your work environment to your needs. Spending an hour to set up some shortcuts is virtually always a good time investment. Then you … 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
How to test the solutions python3 submit.py python_lab.py Lab 1: Introduction to Python—sets, lists, dictionaries, and comprehensions Python provides some simple data structures for grouping together multiple values, and integrates … Read more
This is an overview of the most common git commands. I strongly recommend knowing its basic and using it to anybody writing code, whether alone or particularly within a team. … 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
A reproducible R / Python approach to getting up and running quickly on GCloud with GPUs in Tensorflow “A high view of a sea of clouds covering a mountain valley … 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
Let’s create a simple WebServer to control things in your home. There are a lot of ways to do that. For example, on my tutorial: IoT — Controlling a Raspberry Pi Robot … Read more
I am a long time R user and I like R a lot. Coding in RStudio is a breeze and most every problem already has an associated package with a … Read more
While (personal) computers have become increasingly powerful over the last years there are still lots of workloads that easily bring even the best workstation to its knees. Running huge Monte-Carlo … Read more
Azure Container Registry is the Microsoft equivalent to private Dockerhub repositories. First, I will show you how to quickly push an image to Azure Container Registry. In a second step, … Read more
We rely heavily on Microsoft’s cloud platform Azure during for our analytics workloads at the Austrian Postal Service. Azure has grown rapidly over the past few years and is adding … 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
Many organizations have become adept at identifying what they need from software development projects, based on a keen understanding of their business goals. Even so, they’re often surprised to find … 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
Murphy’s Law Probably one of the most famous of all laws, mostly because it is not only applicable to Software Development. If something can go wrong, it will. First derivation: … Read more
Don’t get confused by its name! It is a classification not a regression algorithm. It is used to estimate discrete values (binary values like 0/1, yes/no, true/false ) based on … Read more
Broadly, there are three types of Machine Learning Algorithms.. 1. Supervised Learning How it works: This algorithm consist of a target or outcome variable (or dependent variable) which is to … Read more