Tableau for Beginners – Data Visualisation made easy

There are multiple Software that are available now at instant access which assist in such easy visualisations and one tool that we are going to cover in this article is Tableau.

Automated Machine Learning for Professionals

There are a variety of new Automated Machine Learning (AML) platforms emerging that led us recently to ask if we’d be automated and unemployed any time soon. In this article we’ll cover the “Professional AML tools”. They require that you be fluent in R or Python which means that Citizen Data Scientists won’t be using them. They also significantly enhance productivity and reduce the redundant and tedious work that’s part of model building.

Seq2seq for NLP: Encoder-Decoder Framework for Tensorflow

tf-seq2seq is a general-purpose encoder-decoder framework for Tensorflow that can be used for Machine Translation, Text Summarization, Conversational Modeling, Image Captioning, and more.

Best Practices for Feature Engineering

Feature engineering, the process creating new input features for machine learning, is one of the most effective ways to improve predictive models.

Quick Way of Installing all your old R libraries on a New Device

I recently bought a new laptop and began installing essential software all over again, including R of course! And I wanted all the libraries that I had installed in my previous laptop.

Introducing Joyplots

joyplot: a series of histograms, density plots or time series for a number of data segments, all aligned to the same horizontal scale and presented with a slight overlap.

ggplot2 – Easy way to mix multiple graphs on the same page

This article will show you, step by step, how to combine multiple ggplots on the same page, as well as, over multiple pages, using helper functions available in the following R package: ggpubr R package, cowplot and gridExtra. We’ll also describe how to export the arranged plots to a file.

Navigating the R Package Universe

Earlier this month, I, along with John Nash, Spencer Graves, and Ludovic Vannoorenberghe, organized a session at useR!2017 focused on discovering, learning about, and evaluating R packages. You can check out the recording of the session.

Jupyter Notebook Keyboard Shortcuts – Cheat Sheet

When people discover a Jupyter keyboard shortcut, they often say “I wish I’d known this earlier!” That’s why Jake VanderPlas created a handy Jupyter keyboard shortcut cheat sheet. All the shortcuts you need when building out your Jupyter Notebook.

How to use AI for marketing automation

When you can automate something without loss of quality, do it. At Statsbot, we used to help automating analytical routine using AI approaches. Analytics cannot be separated from marketing, and we decided to tell how AI can help with marketing automation as well. Just best approaches with powerful tools.

The Machine Learning Abstracts (Part 1): Classification

Ever applied for a credit card and been approved in seconds? Ever read about fraud detection in banks? Ever wondered how your email filters spam? Ever curious about how cameras detect faces? It’s all classification Classification is the process of categorizing or “classifying” some items into a predefined set of categories or “classes”. It is exactly the same even when a machine does so. Let’s dive a little deeper.

Machine Learning and Misinformation

Communication is an essential pillar of society. Humanity’s progression over the past millennium was largely driven by the development and evolution of communication as a tool for distributing siloed thoughts from one individual to others. Communication is naively defined as content and the mode of transmission — symbols manifested as images, language transmitted through speech and writing, digital files sent through the internet. These are methods through which we communicate thoughts, ideas, facts, and opinions. New forms of communication emerge to expand the lexicon of thought and reduce the friction required to create and transmit content. Computers are unique as communication tools because they are used for the creation, transmission, and consumption of content. Most tools before the computer aided in one of these categories, but the digital computer quickly became the de facto platform for media. This unified tool simplifies the process for communicating; you know that what you create on your screen can be instantly reproduced on another’s screen. But the goal is not simply to transmit bits from device to device, the goal is to transmit ideas from one person to another. Early practitioners in the field of Interaction Design espoused human-computer symbiosis1, a tight bond between human and machine that transcends the capabilities of either individually. As communication devices, computers would facilitate a level of understanding between people that was previously only accessible to skilled writers, speakers, and artists. Computational creation reduces the skill needed to craft content that resembles the ideal form as it exists in your head; colors can be selected from a color picker instead of requiring an individual to understand the complex nature of mixing different paints to achieve a certain palette. The trend is towards uninhibited creation of a sort that only exists in the mind.

Classifying traffic signs with Apache MXNet: An introduction to computer vision with neural networks

Step-by-step instructions to implement a convolutional neural net, using a Jupyter Notebook. Although there are many deep learning frameworks, including TensorFlow, Keras, Torch, and Caffe, Apache MXNet in particular is gaining popularity due to its scalability across multiple GPUs. In this blog post, we’ll tackle a computer vision problem: classifying German traffic signs using a convolutional neural network. The network takes a color photo containing a traffic sign image as input, and tries to identify the type of sign.