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LM101-052: How to Use the Kernel Trick to Make Hidden Units Disappear Episode Summary: Today, we discuss a simple yet powerful idea which began popular in the machine learning literature in the 1990s which is called “The Kernel Trick”. The basic idea behind “The Kernel Trick” is that an impossible machine learning problem can be transformed into an… Read More »
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LM101-051: How to Use Radial Basis Function Perceptron Software for Supervised Learning [Rerun] Episode Summary: In this episode we describe how to download and use free nonlinear machine learning software for implementing a Perceptron learning machine with a single layer of Radial Basis Function hidden units for the purposes of supervised learning. Show Notes: Welcome to the 51st podcast… Read More »
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LM101-050: How to Use Linear Machine Learning Software to Make Predictions (Linear Regression Software)[RERUN] Episode Summary: In this episode we describe how to download and use free linear machine learning software to make predictions for classifying flower species using a famous machine learning data set. This is a RERUN of Episode 13. Show Notes: Hello everyone! Welcome to… Read More »
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LM101-047: How To Build a Support Vector Machine to Classify Patterns (Rerun) Episode Summary: In this RERUN of the 32nd episode of Learning Machines 101, we introduce the concept of a Support Vector Machine. We explain how to estimate the parameters of such machines to classify a pattern vector as a member of one of two categories… Read More »
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LM101-041: What happened at the 2015 Neural Information Processing Systems Deep Learning Tutorial? Episode Summary: This is the first of a short subsequence of podcasts which provides a summary of events at the recent 2015 Neural Information Processing Systems Conference. This is one of the top conferences in the field of Machine Learning. This episode introduces the Neural… Read More »
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LM101-034: How to Use Nonlinear Machine Learning Software to Make Predictions (Feedforward Perceptrons with Radial Basis Functions)[Rerun] Episode Summary: In this episode we describe how to download and use free nonlinear machine learning software which is more advanced than the linear machine software introduced in Episode 13. Show Notes: Welcome to the 34th podcast in the podcast series… Read More »
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LM101-033: How to Use Linear Machine Learning Software to Make Predictions (Linear Regression Software)[RERUN] Episode Summary: In this episode we describe how to download and use free linear machine learning software to make predictions for classifying flower species using a famous machine learning data set. This is a RERUN of Episode 13. Show Notes: Hello everyone! Welcome… Read More »
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LM101-032: How To Build a Support Vector Machine to Classify Patterns Episode Summary: In this 32nd episode of Learning Machines 101, we introduce the concept of a Support Vector Machine. We explain how to estimate the parameters of such machines to classify a pattern vector as a member of one of two categories as well as identify special… Read More »
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LM101-025: How to Build a Lunar Lander Autopilot Learning Machine (adaptive control) Episode Summary: In this episode we consider the problem of learning when the actions of the learning machine can alter the characteristics of the learning machine’s statistical environment. We illustrate the solution to this problem by designing an autopilot for a lunar lander module that learns… Read More »
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Episode Summary: In this episode we introduce the concept of gradient descent which is the fundamental principle underlying learning in the majority of machine learning algorithms. Show Notes: Hello everyone! Welcome to the sixteenth podcast in the podcast series Learning Machines 101. In this series of podcasts my goal is to discuss important concepts of artificial intelligence and… Read More »
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Episode Summary: In this episode we describe how to build a machine that can learn any given pattern of inputs and generate any desired pattern of outputs when it is possible to do so! Show Notes: Hello everyone! Welcome to the fifteenth podcast in the podcast series Learning Machines 101. In this series of podcasts my goal is… Read More »
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Episode Summary: In this episode we describe how to build a machine that can take any given pattern of inputs and generate any desired pattern of outputs! Show Notes: Hello everyone! Welcome to the fourteenth podcast in the podcast series Learning Machines 101. In this series of podcasts my goal is to discuss important concepts of artificial intelligence… Read More »
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Episode Summary: In this episode we describe how to download and use free linear machine learning software to make predictions for classifying flower species using a famous machine learning data set. Show Notes: Hello everyone! Welcome to the thirteenth podcast in the podcast series Learning Machines 101. In this series of podcasts my goal is to discuss important… Read More »
