Recursive (not Recurrent!) Neural Networks in TensorFlow
Learn how to implement recursive  neural networks in TensorFlow, which can be used to learn tree-like structures, or directed acyclic graphs.
on Jun 30, 2016 in
Neural Networks , TensorFlow
Mining Twitter Data with Python Part 5: Data Visualisation Basics
Part 5 of this series takes on data visualization, as we look to make sense of our data and highlight interesting insights.
on Jun 29, 2016 in
D3.js , Data Visualization , Python , Social Media , Social Media Analytics , Text Mining , Twitter
Mining Twitter Data with Python Part 4: Rugby and Term Co-occurrences
Part 4 of this series employs some of the lessons learned thus far to analyze tweets related to rugby matches and term co-occurrences.
on Jun 27, 2016 in
Python , Social Media , Social Media Analytics , Text Mining , Twitter
Improving Nudity Detection and NSFW Image Recognition
This post discussed improvements made in a tricky machine learning classification problem: nude and/or NSFW, or not?
on Jun 25, 2016 in
Algorithmia , Algorithms , Classification
Regularization in Logistic Regression: Better Fit and Better Generalization?
A discussion on regularization in logistic regression, and how its usage plays into better model fit and generalization.
on Jun 24, 2016 in
Cost Function , Logistic Regression , Machine Learning , Regression , Regularization
A Visual Explanation of the Back Propagation Algorithm for Neural Networks
A concise explanation of backpropagation for neural networks is presented in elementary terms, along with explanatory visualization.
on Jun 17, 2016 in
Algorithms , Backpropagation , Explanation , Machine Learning , Neural Networks
Nutrition & Principal Component Analysis: A Tutorial
A great overview of Principal Component Analysis (PCA), with an example application in the field of nutrition.
on Jun 16, 2016 in
Algobeans , Feature Selection , Food , Nutrition , PCA
7 Steps to Mastering SQL for Data Science
Follow these 7 steps to go from SQL data science newbie to seasoned practitioner quickly. No nonsense, just the necessities.
on Jun 16, 2016 in
7 Steps , Data Science , Database , Relational Databases , SQL
Mining Twitter Data with Python Part 1: Collecting Data
Part 1 of a 7 part series focusing on mining Twitter data for a variety of use cases. This first post lays the groundwork, and focuses on data collection.
on Jun 15, 2016 in
Python , Social Media , Social Media Analytics , Twitter
How to Select Support Vector Machine Kernels
Support Vector Machine kernel selection can be tricky, and is dataset dependent. Here is some advice on how to proceed in the kernel selection process.
on Jun 13, 2016 in
Machine Learning , Support Vector Machines
Apache Spark Key Terms, Explained
An overview of 13 core Apache Spark concepts, presented with focus and clarity in mind. A great beginner's overview of essential Spark terminology.
on Jun 13, 2016 in
Apache Spark , Databricks , Dataset , Explained , Key Terms , RDD , Tungsten
Top NoSQL Database Engines
An overview of the top 5 NoSQL database engines in use today, including examples of key-value, column-oriented, graph, and document paradigms.
on Jun 10, 2016 in
Cassandra , Database , HBase , MongoDB , Neo4j , NoSQL
Cloud Computing Key Terms, Explained
A concise overview of 20 core cloud computing ecosystem concepts. The focus here is on the terminology, not The Big Picture.
on Jun 9, 2016 in
AWS , Cloud , Cloud Computing , Explained , Key Terms , PaaS , SaaS
5 Best Practices for Big Data Security
Lack of data security can not only result in financial losses, but may also damage the reputation of organizations. Take a look at some of the most important data security best practices that can reduce the risks associated with analyzing a massive amount of data.
on Jun 9, 2016 in
Best Practices , Big Data , Security
Data Science of Variable Selection: A Review
There are as many approaches to selecting features as there are statisticians since every statistician and their sibling has a POV or a paper on the subject. This is an overview of some of these approaches.
on Jun 7, 2016 in
Algorithms , Big Data , Feature Selection , Statistics
What is the Difference Between Deep Learning and “Regular” Machine Learning?
Another concise explanation of a machine learning concept by Sebastian Raschka. This time, Sebastian explains the difference between Deep Learning and "regular" machine learning.
on Jun 3, 2016 in
Convolutional Neural Networks , Deep Learning