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LM101-034: How to Use Nonlinear Machine Learning Software to Make Predictions (Feedforward Perceptrons with Radial Basis Functions)[Rerun] episode artwork

EPISODE · Aug 25, 2015 · 29 MIN

LM101-034: How to Use Nonlinear Machine Learning Software to Make Predictions (Feedforward Perceptrons with Radial Basis Functions)[Rerun]

from Learning Machines 101

<p class="MsoNormal" style="text-indent:0in;mso-pagination:widow-orphan; mso-layout-grid-align:none;text-autospace:none"><span style="font-size:10.0pt; font-family:"Courier New"">Welcome to the 34th podcast in the podcast series Learning Machines 101 titled <p class="MsoNormal" style="text-indent:0in;mso-pagination:widow-orphan; mso-layout-grid-align:none;text-autospace:none"><span style="font-size:10.0pt; font-family:"Courier New"">"How to Use Nonlinear Machine Learning Software to Make Predictions". <p class="MsoNormal" style="text-indent:0in;mso-pagination:widow-orphan; mso-layout-grid-align:none;text-autospace:none"><span style="font-size:10.0pt; font-family:"Courier New"">This particular podcast is a RERUN of Episode 20 and describes step by step how to download free software which can be used to make predictions using a feedforward artificial neural network whose hidden units are radial basis functions. This is essentially a nonlinear regression modeling problem. Check out: www.learningmachines101.comand follow us on twitter: @lm101talk

Episode metadata supplied by the publisher feed · Published Aug 25, 2015

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LM101-034: How to Use Nonlinear Machine Learning Software to Make Predictions (Feedforward Perceptrons with Radial Basis Functions)[Rerun]

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