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Dylan StoreyDecember 3, 2018

Random Forests, Decision Trees, and Ensemble Methods Explained

Data scientist Dylan Storey goes over how to implement a random forest from the ground up as well as how to train, make a prediction, and compare a random forest to a decision tree.

Padmakumar NambiarNovember 26, 2018

How Deep Neural Nets Really Learn

Padmakumar Nambiar, a software development director at Oracle, dives into the field of deep learning and its biggest challenges. Learn how catastrophic forgetting, the tendency of deep learning...

Greg DeVoreNovember 15, 2018

Supervised Learning With Python

Boeing Engineer Greg DeVore gives an introduction to supervised learning in Python, including how to choose the appropriate model for a regression or classification problem, as well as how to...

Skander HannachiNovember 8, 2018

Decomposition-Based Approaches to Time Series Forecasting

Nordstrom Data Scientist Skander Hannachi walks us through three approaches to forecasting using decomposition with R: Seasonal and Trend decomposition using LOESS, Bayesian structural time series,...

Supreet OberoiOctober 29, 2018

SAX and Matrix Profile Techniques for Root Cause Analysis

Oracle VP of IoT and Big Data Applications Supreet Oberoi walks us through an use case using Matrix Profile and SAX to perform Root Cause Analysis.

Bryan JohnsonOctober 22, 2018

Graph Computations With Apache Spark

Oracle Data Cloud Principal Data Scientist Bryan Johnson demonstrates how to use Apache Spark to perform graph computations.

Jonathan RegensteinOctober 15, 2018

How To Calculate The Standard Deviation Of A Financial Portfolio In R, Part 2: Component...

RStudio's Jonathan Regenstein dives into part two of his three-part series on calculating the volatility of a financial portfolio using R. In this post, learn how to investigate the degree to which a...

Blaine BatemanSeptember 17, 2018

Challenges of Generalization in Machine Learning

EAF LLC Founder & Chief Data Engineer Blaine Bateman breaks down the efficacy of using validation performance to choose a model, and k-fold validation to predict future accuracy.

Vinay KaragodSeptember 6, 2018

How to Handle Imbalanced Data: An Overview

Microsoft's Vinay Karagod provides an overview of several methods for handling data imbalances that can make data science projects a lot more challenging.

David Ellison, PhDAugust 9, 2018

Fraud Detection Using Autoencoders in Keras with a TensorFlow Backend

Lenovo's David Ellison explains how autoencoders in Keras can be used to detect fraud. Read the tutorial the learn this invaluable TensorFlow application.