"References" is our generic tag for questions seeking information about books, papers, presentations, videos of lectures, on-line tutorials, etc., regarding any subject matter that is on-topic for Data Science.
Questions tagged [reference-request]
76 questions
57
votes
8 answers
Why do internet companies prefer Java/Python for data scientist job?
I see a many times in job description for data scientist asking for Python/Java experience and disregard R. Below is a personal email I received from chief data scientist of a company I applied for through linkedin.
X, Thanks for connecting and…
StatguyUser
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29
votes
4 answers
Books about the "Science" in Data Science?
What are the books about the science and mathematics behind data science? It feels like so many "data science" books are programming tutorials and don't touch things like data generating processes and statistical inference. I can already code, what…
Anton
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18
votes
4 answers
Data science / machine learning books for mathematicians
I have found other requests for references here. In particular in:
Where to start, which books
and
Books about the "Science" in Data Science?
I have given a glance to:
Artificial Intelligence: A Modern Approach (Russel & Norvig)
Machine Learning:…
Contactomorph
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17
votes
5 answers
Beginner math books for Machine Learning
I'm a Computer Science engineer with no background in statistics or advanced math.
I'm studying the book Python Machine Learning by Raschka and Mirjalili, but when I tried to understand the math of the Machine Learning, I wasn't able to understand…
Tantaros
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16
votes
7 answers
Data Science Podcasts?
What are some podcasts which are related to data science?
This is a similar question to the reference request question on CrossValidated.
Details/rules:
The podcasts (the theme and the episodes) should be related to data science. (For example: A…
Dawny33
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10
votes
4 answers
Math PhD (Nonlinear Programming) switching to Data Science?
I am a math Ph.D. student who is interested in going to the industry as a Data Scientist after graduation. I will briefly give some background on my education before posing my question, so that it is better understood:
Maths Coursework:
This has…
John D
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9
votes
3 answers
Sentiment Analysis Tutorial
I am trying to understand sentiment analysis and how to apply it using any language (R, Python etc). I would like to know if there is a good place on internet for tutorial that I can follow. I googled, but I wasn't very much satisfied because they…
KurioZ7
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8
votes
1 answer
Who invented the concept of over-fitting?
I list the references that I found so far.
Shortly, the first appearance of the term was in 1670, first appearance in in close meaning was in 1827, first appearance in a biological paper was in 1923 and first appearance in statistics was in…
DaL
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8
votes
1 answer
Keras categorical_crossentropy loss (and accuracy)
When training a neural network with keras for the categorical_crossentropy loss, how exactly is the loss defined? I expect it to be the average over all samples of
$$\textstyle\text{loss}(p^\text{true}, p^\text{predict}) = -\sum_i p_i^\text{true}…
user66081
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8
votes
4 answers
Which book is a standard for introduction to genetic algorithms?
I have heard of genetic algorithms, but I have never seen practical examples and I've never got a systematic introduction to them.
I am now looking for a textbook which introduces genetic algorithms in detail and gives practical examples how they…
Martin Thoma
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7
votes
1 answer
data science / machine learning resources?
In a few weeks I'm starting a new job that will be involved in machine learning and data science.
I have a masters degree in probability / mathematics but I have no knowledge of machine learning and data science.
Are there any online resources like…
lezebulon
- 179
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7
votes
5 answers
Mastering NLP: Reading List
I've searched the web and there are hundreds of recommendations on what to read. The time moves on and new better quality techniques are published, so I would like to know what is relevant in 2018?
My background is 4 years of BSc in Maths & Stats…
GRS
- 173
- 9
7
votes
3 answers
Is there any proven disadvantage of transfer learning for CNNs?
Suppose I know that I want to use a ResNet-101 architecture for my specific problem. There are ReseNet-101 models trained on ImageNet.
Is there any disadvantage of using those pre-trained models and just resetting the last (few) layers to match the…
Martin Thoma
- 18,630
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5
votes
4 answers
Features & Models to compute the probability of certain customer accepting an offer/product from a bank?
What are the features & models that can be used to compute the probability of a certain customer accepting an offer/product from a bank?
After some research, I came to know of what is called 'Propensity Scoring' and it's definition is very relevant…
hshihab
- 151
- 4
4
votes
1 answer
List of NLP challenges
Is there any comprehensive list of past, current and future NLP challenges?
E.g. for NLP conferences, Joel Tetreault's unofficially official conference calendar and WikiCFP are pretty good.
The "Competitions and Challenges" page on the ACL wiki…
Franck Dernoncourt
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