machine learning explanations, mid-sentence

What this neuron does

This neuron lights up on textbook-style sentences about machine learning, especially on words that come right before words like 'training' or 'learn'. Turning it up made the text drift into unrelated topics like weather and news, so the link to the topic is clear from the examples but not from the steering.

Written by Claude from this neuron's activations and steering outputs. Confidence: medium. Think it is wrong? Flag it (opens a prefilled issue on GitHub).

Fires most on

The text windows where this neuron's activation was highest. Amber marks positive activation; the outlined token is the peak. Hover a token for its strength.

1. #1 peak

   form of machine learning that uses neural networks with many “deep” layers between the input and output nodes. By training a network on a large data set, a model is created that can be used to make accurate predictions based on input data. In

2. #2 peak

   domain of humans, from diagnosing medical conditions to driving cars.⏎One of the most exciting aspects of AI is its ability to learn and adapt. Machine learning algorithms can analyze vast amounts of data to identify patterns and make predictions, and they improve with

3. #3 peak

   the input-output pair. It is called supervised learning because the process of an algorithm learning from the training dataset can be thought of as a teacher supervising the learning process.⏎

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   Machine Learning techniques, so the below list is not exhaustive.⏎Supervised machine learning⏎This technique uses historical data (i.e. data that was generated beforehand), to understand patterns and then infer values from new observations. Supervised learning parameters are crucial

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   HyperParameters:⏎Gradient descent takes small steps to reduce the loss of a model. Gradient descent algorithms multiply the gradient by a scalar known as the learning rate

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   Recognition(how Google Assistant or Siri listens to your commands) or Computer Vision(how Google Lens works).⏎Machine Learning is the field of study that will enable computers to learn without being explicitly programmed.⏎Machine Learning is a subset of Artificial Intelligence.⏎Common

Steering

Push this neuron up or down while the model writes, and watch what changes. The outputs were generated ahead of time, so nothing runs in your browser.

Most negative on

Where the activation went furthest below zero. Blue marks negative activation. Many neurons mean something different in each direction.

1. #1 peak

   Frequent Itemset Mining Methods. Classification: Classification by Decision Tree Induction – Bayesian Classification – Rule based Classification - Prediction – Accuracy and Error Measures⏎Cluster Analysis – Types

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   of Data in Cluster Analysis – Categorization of clustering Methods – Partition Methods - Outlier Analysis – Mining Data Streams – Social Network Analysis – Mining the World Wide

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   , “Introduction to Data Mining with Case Studies”, 2nd Edition, PHI.⏎Students will be able to:⏎1. Explain the concepts in data mining and KDD, recognizing issues in Data Mining⏎2. Practice the preprocessing operations of Data

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   with unlabelled data.⏎Some applications of unsupervised machine learning techniques include: clustering (grouping coherent segments of customers, or grouping logistic pick-up points), anomaly detection (detecting issues in operational or industrial processes), association mining (customer

Which neurons in earlier layers feed this one, and which later ones it feeds. Amber links excite, blue links suppress; longer bars are stronger.

Activation histogram

How often this neuron fires at each strength. Almost always it does close to nothing (the tall bars in the middle); the snippets above are the rare moments it fired hard, amber for positive and blue for negative.

Logit lens

The words this neuron nudges the model toward (amber) or away from (blue) when it fires. A hint, not a label: many neurons work through later layers instead.