Scaling neural networks
$begingroup$
While using Neural Networks (TensorFlow: Deep Neural Regressor), when increasing your training data size from a sample to the whole data (say a 10x larger dataset), what changes should you make to the model architecture (deeper/wider), learning rate and hyper parameters in general?
Is it purely trial and error or is there some heuristic logic to apply in making these changes?
machine-learning neural-network deep-learning tensorflow hyperparameter-tuning
asked 2 mins ago
SharanSharan
1
New contributor
Sharan is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
While using Neural Networks (TensorFlow: Deep Neural Regressor), when increasing your training data size from a sample to the whole data (say a 10x larger dataset), what changes should you make to the model architecture (deeper/wider), learning rate and hyper parameters in general?
Is it purely trial and error or is there some heuristic logic to apply in making these changes?
machine-learning neural-network deep-learning tensorflow hyperparameter-tuning
asked 2 mins ago
SharanSharan
1
New contributor
Sharan is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
While using Neural Networks (TensorFlow: Deep Neural Regressor), when increasing your training data size from a sample to the whole data (say a 10x larger dataset), what changes should you make to the model architecture (deeper/wider), learning rate and hyper parameters in general?
Is it purely trial and error or is there some heuristic logic to apply in making these changes?
machine-learning neural-network deep-learning tensorflow hyperparameter-tuning
asked 2 mins ago
SharanSharan
1
New contributor
Sharan is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
While using Neural Networks (TensorFlow: Deep Neural Regressor), when increasing your training data size from a sample to the whole data (say a 10x larger dataset), what changes should you make to the model architecture (deeper/wider), learning rate and hyper parameters in general?
Is it purely trial and error or is there some heuristic logic to apply in making these changes?
machine-learning neural-network deep-learning tensorflow hyperparameter-tuning
machine-learning neural-network deep-learning tensorflow hyperparameter-tuning
asked 2 mins ago
SharanSharan
1
New contributor
Sharan is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 mins ago
SharanSharan
1
New contributor
Sharan is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 mins ago
SharanSharan
1
New contributor
Sharan is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 mins ago
SharanSharan
1
asked 2 mins ago
SharanSharan
1
1
New contributor
Sharan is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Sharan is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Sharan is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
add a comment |
add a comment |
0
active
oldest
votes
Your Answer
StackExchange.ifUsing("editor", function () {
return StackExchange.using("mathjaxEditing", function () {
StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix) {
StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
});
});
}, "mathjax-editing");
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "557"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});
function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: false,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: null,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});
}
});
Sharan is a new contributor. Be nice, and check out our Code of Conduct.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fdatascience.stackexchange.com%2fquestions%2f47712%2fscaling-neural-networks%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
0
active
oldest
votes
0
active
oldest
votes
active
oldest
votes
active
oldest
votes
Sharan is a new contributor. Be nice, and check out our Code of Conduct.
Sharan is a new contributor. Be nice, and check out our Code of Conduct.
Sharan is a new contributor. Be nice, and check out our Code of Conduct.
Sharan is a new contributor. Be nice, and check out our Code of Conduct.
Thanks for contributing an answer to Data Science Stack Exchange!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
Use MathJax to format equations. MathJax reference.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fdatascience.stackexchange.com%2fquestions%2f47712%2fscaling-neural-networks%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
