Efficient self study plan Announcing the arrival of Valued Associate #679: Cesar Manara Planned maintenance scheduled April 23, 2019 at 23:30 UTC (7:30pm US/Eastern) 2019 Moderator Election Q&A - Questionnaire 2019 Community Moderator Election ResultsEfficient dynamic clusteringHow to create Self learning data productHow to self-learn data science?How to approach a Data Science case study question?Classification with millions of records, thousands of categories - keep memory use efficient?recommendations for self-study in ML/Deep Learning/the underlying mathLongitudinal study - conversion long to wide - implicationsHow to plan a model analysis that avoids overfitting?Feasibility study of machine learning
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Efficient self study plan
Announcing the arrival of Valued Associate #679: Cesar Manara
Planned maintenance scheduled April 23, 2019 at 23:30 UTC (7:30pm US/Eastern)
2019 Moderator Election Q&A - Questionnaire
2019 Community Moderator Election ResultsEfficient dynamic clusteringHow to create Self learning data productHow to self-learn data science?How to approach a Data Science case study question?Classification with millions of records, thousands of categories - keep memory use efficient?recommendations for self-study in ML/Deep Learning/the underlying mathLongitudinal study - conversion long to wide - implicationsHow to plan a model analysis that avoids overfitting?Feasibility study of machine learning
$begingroup$
I am hoping for a bit of guidance from experienced practitioners / academics.
I want to work through the Bishop ML book, but have minimal background.
What is the fastest way to get the pre-requisites (specific books would be appreciated)?
From searching around I found this potential self-study path:
Statistical Inference - Casella / Berger
Probability Theory and Examples - Durrett
Linear Algebra - Hoffman / Kunze
I checked these books out from the library, but they will take me over a year to work through thoroughly, so it does not seem to be practical.
I have searched around on the internet, but most of the advice doesn't list any specific books, just what subjects I should learn.
About me
Graduated in an unrelated discipline many years ago
Willing to dedicate many hours to this (I am doing this to build a background for a degree in machine learning)
I can code pretty well due to my job
machine-learning statistics self-study mathematics
asked Apr 4 at 10:28
Convex RomanceConvex Romance
133
$endgroup$
add a comment |
$begingroup$
I am hoping for a bit of guidance from experienced practitioners / academics.
I want to work through the Bishop ML book, but have minimal background.
What is the fastest way to get the pre-requisites (specific books would be appreciated)?
From searching around I found this potential self-study path:
Statistical Inference - Casella / Berger
Probability Theory and Examples - Durrett
Linear Algebra - Hoffman / Kunze
I checked these books out from the library, but they will take me over a year to work through thoroughly, so it does not seem to be practical.
I have searched around on the internet, but most of the advice doesn't list any specific books, just what subjects I should learn.
About me
Graduated in an unrelated discipline many years ago
Willing to dedicate many hours to this (I am doing this to build a background for a degree in machine learning)
I can code pretty well due to my job
machine-learning statistics self-study mathematics
asked Apr 4 at 10:28
Convex RomanceConvex Romance
133
$endgroup$
add a comment |
$begingroup$
I am hoping for a bit of guidance from experienced practitioners / academics.
I want to work through the Bishop ML book, but have minimal background.
What is the fastest way to get the pre-requisites (specific books would be appreciated)?
From searching around I found this potential self-study path:
Statistical Inference - Casella / Berger
Probability Theory and Examples - Durrett
Linear Algebra - Hoffman / Kunze
I checked these books out from the library, but they will take me over a year to work through thoroughly, so it does not seem to be practical.
I have searched around on the internet, but most of the advice doesn't list any specific books, just what subjects I should learn.
About me
Graduated in an unrelated discipline many years ago
Willing to dedicate many hours to this (I am doing this to build a background for a degree in machine learning)
I can code pretty well due to my job
machine-learning statistics self-study mathematics
asked Apr 4 at 10:28
Convex RomanceConvex Romance
133
$endgroup$
I am hoping for a bit of guidance from experienced practitioners / academics.
I want to work through the Bishop ML book, but have minimal background.
What is the fastest way to get the pre-requisites (specific books would be appreciated)?
From searching around I found this potential self-study path:
Statistical Inference - Casella / Berger
Probability Theory and Examples - Durrett
Linear Algebra - Hoffman / Kunze
I checked these books out from the library, but they will take me over a year to work through thoroughly, so it does not seem to be practical.
I have searched around on the internet, but most of the advice doesn't list any specific books, just what subjects I should learn.
About me
Graduated in an unrelated discipline many years ago
Willing to dedicate many hours to this (I am doing this to build a background for a degree in machine learning)
I can code pretty well due to my job
machine-learning statistics self-study mathematics
machine-learning statistics self-study mathematics
asked Apr 4 at 10:28
Convex RomanceConvex Romance
133
asked Apr 4 at 10:28
Convex RomanceConvex Romance
133
asked Apr 4 at 10:28
Convex RomanceConvex Romance
133
asked Apr 4 at 10:28
Convex RomanceConvex Romance
133
asked Apr 4 at 10:28
Convex RomanceConvex Romance
133
133
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
$begingroup$
I'm not super familiar with Bishop, but it looks like Durrett, which deals with measure-theoretic probability, would be overkill. Plus you would probably have to add real analysis to your prerequisites. I would just work through the first 4-5 Casella chapters on probability and random variables.
You probably also don't need to go through the whole linear algebra book to get started. Just make sure you understand the basic matrix operations well enough to deal with multivariate calculus (ex. taking multivariate derivatives and computing multivariate integrals).
The second half of Casella would likely be useful, but I suspect not strictly necessary.
I think if you can handle those things you'll have most of Bishop covered; you can always pick up more as needed.
answered Apr 4 at 23:37
Unrefracted_HooloovooUnrefracted_Hooloovoo
262
$endgroup$
$begingroup$
Thanks this makes a lot more sense. Since I there are a lot of "unknown unknowns" in terms of knowledge for me, having a clear answer like this is very helpful.
$endgroup$
– Convex Romance
Apr 5 at 9:30
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
I'm not super familiar with Bishop, but it looks like Durrett, which deals with measure-theoretic probability, would be overkill. Plus you would probably have to add real analysis to your prerequisites. I would just work through the first 4-5 Casella chapters on probability and random variables.
You probably also don't need to go through the whole linear algebra book to get started. Just make sure you understand the basic matrix operations well enough to deal with multivariate calculus (ex. taking multivariate derivatives and computing multivariate integrals).
The second half of Casella would likely be useful, but I suspect not strictly necessary.
I think if you can handle those things you'll have most of Bishop covered; you can always pick up more as needed.
answered Apr 4 at 23:37
Unrefracted_HooloovooUnrefracted_Hooloovoo
262
$endgroup$
$begingroup$
Thanks this makes a lot more sense. Since I there are a lot of "unknown unknowns" in terms of knowledge for me, having a clear answer like this is very helpful.
$endgroup$
– Convex Romance
Apr 5 at 9:30
add a comment |
$begingroup$
I'm not super familiar with Bishop, but it looks like Durrett, which deals with measure-theoretic probability, would be overkill. Plus you would probably have to add real analysis to your prerequisites. I would just work through the first 4-5 Casella chapters on probability and random variables.
You probably also don't need to go through the whole linear algebra book to get started. Just make sure you understand the basic matrix operations well enough to deal with multivariate calculus (ex. taking multivariate derivatives and computing multivariate integrals).
The second half of Casella would likely be useful, but I suspect not strictly necessary.
I think if you can handle those things you'll have most of Bishop covered; you can always pick up more as needed.
answered Apr 4 at 23:37
Unrefracted_HooloovooUnrefracted_Hooloovoo
262
$endgroup$
$begingroup$
Thanks this makes a lot more sense. Since I there are a lot of "unknown unknowns" in terms of knowledge for me, having a clear answer like this is very helpful.
$endgroup$
– Convex Romance
Apr 5 at 9:30
add a comment |
$begingroup$
I'm not super familiar with Bishop, but it looks like Durrett, which deals with measure-theoretic probability, would be overkill. Plus you would probably have to add real analysis to your prerequisites. I would just work through the first 4-5 Casella chapters on probability and random variables.
You probably also don't need to go through the whole linear algebra book to get started. Just make sure you understand the basic matrix operations well enough to deal with multivariate calculus (ex. taking multivariate derivatives and computing multivariate integrals).
The second half of Casella would likely be useful, but I suspect not strictly necessary.
I think if you can handle those things you'll have most of Bishop covered; you can always pick up more as needed.
answered Apr 4 at 23:37
Unrefracted_HooloovooUnrefracted_Hooloovoo
262
$endgroup$
I'm not super familiar with Bishop, but it looks like Durrett, which deals with measure-theoretic probability, would be overkill. Plus you would probably have to add real analysis to your prerequisites. I would just work through the first 4-5 Casella chapters on probability and random variables.
You probably also don't need to go through the whole linear algebra book to get started. Just make sure you understand the basic matrix operations well enough to deal with multivariate calculus (ex. taking multivariate derivatives and computing multivariate integrals).
The second half of Casella would likely be useful, but I suspect not strictly necessary.
I think if you can handle those things you'll have most of Bishop covered; you can always pick up more as needed.
answered Apr 4 at 23:37
Unrefracted_HooloovooUnrefracted_Hooloovoo
262
answered Apr 4 at 23:37
Unrefracted_HooloovooUnrefracted_Hooloovoo
262
answered Apr 4 at 23:37
Unrefracted_HooloovooUnrefracted_Hooloovoo
262
answered Apr 4 at 23:37
Unrefracted_HooloovooUnrefracted_Hooloovoo
262
262
$begingroup$
Thanks this makes a lot more sense. Since I there are a lot of "unknown unknowns" in terms of knowledge for me, having a clear answer like this is very helpful.
$endgroup$
– Convex Romance
Apr 5 at 9:30
add a comment |
$begingroup$
Thanks this makes a lot more sense. Since I there are a lot of "unknown unknowns" in terms of knowledge for me, having a clear answer like this is very helpful.
$endgroup$
– Convex Romance
Apr 5 at 9:30
$begingroup$
Thanks this makes a lot more sense. Since I there are a lot of "unknown unknowns" in terms of knowledge for me, having a clear answer like this is very helpful.
$endgroup$
– Convex Romance
Apr 5 at 9:30
$begingroup$
Thanks this makes a lot more sense. Since I there are a lot of "unknown unknowns" in terms of knowledge for me, having a clear answer like this is very helpful.
$endgroup$
– Convex Romance
Apr 5 at 9:30
add a comment |
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