Posts published in “Tutorials”

Querying Data in Spreadsheets, No Database Required

Published September 25, 2016 by Ryan O'Shea

Querying Data in Spreadsheets, No Database Required

When you’re working with lots of data, few tools are more useful than a powerful querying language like SQL. The ability to isolate the data you’re looking for, make useful transformations, and generate statistics…

Zoom with Composable!

Published January 26, 2016 by Lars Fiedler

Zoom with Composable!

We’re proud to announce Composable’s data flow designer now supports full zooming and panning! We think this feature will make working larger more complicated CA apps much easier. Over the…

First hand experience from Uber, Microsoft, Delivery Hero & more – at PAW London
Top practitioners are coming to PAW London, 16-17 Oct 2019, to describe the design, deployment and business impact of their machine learning projects. Register using code KDNUGGETS for a 15% discount on your Predictive Analytics World ticket.
McKinsey: Data Engineer [Wroclaw, Poland]
McKinsey is seeking a Data Engineer in Wroclaw, Poland, to enable effective, highly scalable data analysis pipelines and play a critical role in database design, development, data integration and ingestion, as well as designing ETL architectures using a variety of ETL tools and techniques.
McKinsey: Data Scientist [Wroclaw, Poland]
McKinsey is seeking a Data Scientist in Wroclaw, Poland, to work with McKinsey clients and consulting teams to carry out complex data analysis and modeling, creating a foundation for sound recommendations for client studies and internal projects.
Scaling a Massive State-of-the-art Deep Learning Model in Production
A new NLP text writing app based on OpenAI's GPT-2 aims to write with you -- whenever you ask. Find out how the developers setup and deployed their model into production from an engineer working on the team.
Secrets to a Successful Data Science Interview
Are you puzzled as to what to prepare for data science interviews? That you are reading this document is a reflection of your seriousness in being a successful data scientist.
The Hackathon Guide for Aspiring Data Scientists
This article is an overview of how to prepare for a hackathon as an aspiring data scientist, highlighting the 4 reasons why you should take part in one, along with a series of tips for participation.
Top Stories, Jul 8-14: The Death of Big Data and the Emergence of the Multi-Cloud Era; Training a Neural Network to Write Like Lovecraft
Also: What's wrong with the approach to Data Science?; Introducing Gen: MITs New Language That Wants to be the TensorFlow of Programmable Inference; Top 10 Data Science Leaders You Should Follow; 5 Probability Distributions Every Data Scientist Should Know; XGBoost and Random Forest with Bayesian Optimisation
Introducing Gen: MIT’s New Language That Wants to be the TensorFlow of Programmable Inference
Researchers from MIT recently unveiled a new probabilistic programming language named Gen, a language which allow researchers to write models and algorithms from multiple fields where AI techniques are applied without having to deal with equations or manually write high-performance code.
Pre-training, Transformers, and Bi-directionality
Bidirectional Encoder Representations from Transformers BERT (Devlin et al., 2018) is a language representation model that combines the power of pre-training with the bi-directionality of the Transformer’s encoder (Vaswani et al., 2017). BERT improves the state-of-the-art performance on a wide array of downstream NLP tasks with minimal additional task-specific training.
Top June Stories: 5 Useful Statistics Data Scientists Need to Know; 7 Steps to Mastering Intermediate Machine Learning with Python – 2019 Edition
Also: Data Science Jobs Report 2019: Python Way Up, TensorFlow Growing Rapidly, R Use Double SAS; If you're a developer transitioning into data science, here are your best resources.