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Prompt 1
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Create a webpage to train a single neuron. 
Include a chapter of introduction about linear 
regession and train one neuron for linear regression. 
Also include a chapter of discussion about TensorFlow 
for javascript.

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Prompt 2
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In chapter 1, add a section to draw a picture of 
one neuron with inputs and one output. Add 
easy-to-understand example to explain the model.




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Prompt 3
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Add a new chapter at the end to include libraries 
for defining and training models, and the library 
for web browser visualization. Use the early versions.


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Prompt 4
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In the last chapter , add a button at the end with title
 "Run". When click on it, add javscript code to include 
those two libraries. They will be used later.



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Prompt 5
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Add a chapter of discussion about the data from 
https://storage.googleapis.com/tfjs-tutorials/carsData.json 
and a button to load the dataset.

 Make the dataset to be accessable later. Give the cleaned dataset
the name "cleanedData".

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May be if error
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It says "Dataset loaded! Entries: 0". put your solution together 
so that I can easily copy and paste.

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Prompt 6
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Also include a chapter of visualization of the 
dataset "cleanedData" downloaded early, 
and select Miles_per_gallon:value and Horsepower:value 
for training.

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Promtp 7 
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Add a section at the end, describe how to 
split a dataset to training and testing part. 
Add a button "Split the dataset". When clicking, 
split the dataset downloaded for the button "load dataset" 
and show a summary of the split.

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prompt 8
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Add a new chapter at the end to add a button. 
When clicking, add javascript to define an artificial 
neural network model. Then display a layer information
 of the model. 
Then, add a section to explain what the model is all about,
using picture/animation/illustration to help understand. 
The model will be trained by the training part 
defined above. 

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prompt 9
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Add a chapter to explain how to train the model 
using the dataset "cleanedData". Add a button. 
When click, start train the model using cleanedData. 
Display the training process and show a chart of
the progress.

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Prompt 10
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add a new chapter to explain how to evaluate the trained 
model. Add a button "Evaluate the model". When click, use 
the test part that is obtained from the splitting of the 
cleanedData to evaluate the model.
  Add a chart to show the process of evaluating the model.

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Prompt 11
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Add a new chapter to explain the confusion matrix. Add 
a button "Show confusion matrix". When click, calculate 
and display a chart of the confusion matrix.