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Overview and benchmark of traditional and deep learning models in text classification
In this post, traditional and deep learning models in text classification will be thoroughly investigated, including a discussion into both Recurrent and Convolutional neural networks.
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Why a Professional Association for Data Scientists is a Bad Idea
This post presents the argument against having a professional association for data scientists.
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Modern Graph Query Language – GSQL
This post introduces the prospect of fulfilling the need for a modern graph query language with GSQL
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Using Topological Data Analysis to Understand the Behavior of Convolutional Neural Networks
Neural Networks are powerful but complex and opaque tools. Using Topological Data Analysis, we can describe the functioning and learning of a convolutional neural network in a compact and understandable way.
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5 Data Science Projects That Will Get You Hired in 2018
A portfolio of real-world projects is the best way to break into data science. This article highlights the 5 types of projects that will help land you a job and improve your career.
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Stagraph – a general purpose R GUI, for data import, wrangling, and visualization
Stagraph is a new simple visual interface for R, which focuses on data import, data wrangling and data visualization.
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How to Execute R and Python in SQL Server with Machine Learning Services
Machine Learning Services in SQL Server eliminates the need for data movement - you can install and run R/Python packages to build Deep Learning and AI applications on data in SQL Server.
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Why the Data Lake Matters
This post outlines why the data lake matters, outlining the complexity of a data lake and taking a look at its evolution over time.
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An Intuitive Introduction to Gradient Descent
This post provides a good introduction to Gradient Descent, covering the intuition, variants and choosing the learning rate.
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Technical Content Personalization
Part 3 of this series moves on from segmenting audiences to the technological side of the process.
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