Questions tagged [reference-request]

"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.

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56
votes
8answers
14k views

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 ...
28
votes
4answers
3k views

Books about the "Science" in Data Science? [closed]

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 ...
18
votes
4answers
5k views

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 ...
17
votes
5answers
4k views

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 ...
16
votes
7answers
3k views

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) ...
9
votes
4answers
955 views

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 ...
9
votes
3answers
6k views

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,...
8
votes
1answer
299 views

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 ...
8
votes
1answer
9k views

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}...
7
votes
4answers
6k views

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 ...
7
votes
3answers
5k views

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 ...
7
votes
1answer
669 views

data science / machine learning resources? [closed]

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 ...
7
votes
5answers
964 views

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? ...
4
votes
1answer
7k views

Markov switching models

What are some reference sources for understanding Markov switching models?
4
votes
2answers
1k views

MOOC or book on Deep Learning in Python for someone with a basic knowledge of neural networks

I know the concept of a neural network, and I followed the Machine Learning course by Andrew Ng on Coursera, so I also coded some simple ones. However, I miss all the new tricks which are useful to ...
4
votes
1answer
6k views

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 "...
4
votes
1answer
2k views

Has anyone tried to use the hierarchy of ImageNet?

The classes of ImagNet have a hierarchy. Did anybody try to build a hierarchy of classifiers to use this fact? Searching for "multistage classification" leads to different results.
4
votes
4answers
402 views

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 '...
4
votes
2answers
691 views

Given a machine learning algorithm, what is the minimum size of the training set for it?

I understand that the more data we have, the more reliable is our model trained on that data. I also understand that the more parameters a machine learning model has, the more training data it ...
4
votes
2answers
132 views

Why Gradient methods work in finding the parameters in Neural Networks?

After reading quite a lot of papers (20-30 or so), I feel that I am quite not understanding things. Let us focus on the supervised learnings (for example). Given a set of data $\mathcal{D}_{train}=\{...
4
votes
1answer
125 views

Common Techniques to Generate from a Regression Neural Network Model

I am used to train neural networks that are designed for generation, such as GANs or VAEs. I am wondering what are the common techniques to generate data that would minimize the target/energy learned ...
4
votes
1answer
1k views

What is the best practice to test a ETL pipeline?

In traditional software development practice, before going into production, a piece of code should go through various stages of testing (unit test, integration test, user acceptance test) to secure ...
4
votes
1answer
3k views

Application of ideas from graph theory in machine learning [closed]

I work with neural networks (ConvNNs, DeepNNs, RNNs/LSTMs) for image segmentation and recognition and Genetic Algorithms for some optimization problems. Recently I started to learn some deep graph ...
3
votes
4answers
6k views

Resources on Data Science for Football / Soccer?

I am searching for resources on data science projects which used football/soccer data.
3
votes
1answer
68 views

Outlier/Anomaly Detection History

I have been reading about different methods of anomaly detection, their structure and the way they work. Recently I have been trying to find some scholar articles, writings or books where I can learn ...
3
votes
1answer
36 views

References/tutorials about data mining and machine learning

I am learning data analytics and I wonder if there are some good references and tutorials about machine learning, data analytics and data mining? What I'm searching for is an understandable reference/...
3
votes
1answer
2k views

On the properties of Hyperbolic Tangent Kernel [closed]

How do Hyperbolic Tangent Kernels work? That is what is the intuition behind them? Can you provide proofs and examples for illustration? Hyperbolic Tangent Kernels are defined as: $$ K(x, x^\prime) = ...
2
votes
4answers
3k views

Is there any book for modern optimization in Python?

I was reading Modern Optimization with R (Use R!) and wondering if a book like this exists in Python too? To be precise something that covers stochastic gradient descent and other advanced ...
2
votes
2answers
59 views

Deep Learning to estimate what is beyond the edge

I have an image of some data which is approximately 4,000 x 8,000 pixels. I am interested in finding out if anyone has used a deep learning algorithm to predict what would be on the image if it ...
2
votes
1answer
7k views

What is a good explanation of Non Negative Matrix Factorization?

I am trying to find a resource to understand non-negative matrix factorization. Apart from Wikipedia, I couldn't find anything useful.
2
votes
2answers
595 views

Help me choose a Data Science book in Python [closed]

I've been a Data Scientist for a few years now, but I've only recently started to do most of my work in Python (boy, do I miss ggplot2! But ...
2
votes
1answer
51 views

Rate of convergence - comparison of supervised ML methods

I am working on a project with sparse labelled datasets, and am looking for references regarding the rate of convergence of different supervised ML techniques with respect to dataset size. I know that ...
2
votes
1answer
1k views

Tutorial for restricted Boltzmann machine using PyTorch or Tensorflow?

I am trying to find a tutorial on training Restricted Boltzmann machines on some dataset (e.g. MNIST), using either PyTorch or Tensorflow. The few I found are outdated. Can you recommend any?
2
votes
1answer
245 views

Do 3D bar charts have advantages over 2D bar charts?

I vaguely remember that there was a study / blog post which made a strong point against 3D bar charts. Do you have a source at hand which compares the two - 2D bar charts and 3D bar charts?
2
votes
0answers
74 views

Machine learning for circular sequences

My data are sequences of real numbers $a_0,a_1,...,a_{n-1}$. The length of a sequence is fixed and equals $n$. Each sequence is mapped to a real number $y$ and I want to predict $y$ given the sequence....
2
votes
0answers
87 views

What is the difference between ICR and OCR?

I've just found the term "Intelligent Character Recognition" (ICR) on Wikipedia and other pages. According to Wikipedia: In computer science, intelligent character recognition (ICR) is an ...
2
votes
0answers
26 views

What could be proper terms for a research direction in natural language processing to measure meaningfulness?

For some time, I did assessments to design metrics on how to recognize well-written and meaningful software requirements. Then I decided to work with Stack Overflow question posts because they are a ...
2
votes
1answer
406 views

Data Scientist Consulting Interview Guide [closed]

Does anyone have any books or blogs that specifically sheds light on questions to ask your organization (from a consulting POV) as a data scientist? I am a new data scientist, which I have a ...
2
votes
1answer
258 views

Which Machine Learning book to choose (APM, MLAP or ISL)? [closed]

I'm searching a book as a refresher in machine learning (I have taken a lecture in machine learning sometime ago). I will be applying machine learning in a project. I have searched a lot of books and ...
1
vote
2answers
170 views

What is the relationship between AI and data science?

I think they share a lot (e.g. machine learning is a subset of both, right?), but maybe both have elements the other doesn't have? Could you name some in that case? Or is one a subset of the other? ...
1
vote
1answer
31 views

Classes of neural nets and their applications

Would you say, you could design, tune and/or train any DNN for any application, or do their designs inherently postulate some specialization? Is there such a review? For example, are CNNs better for ...
1
vote
1answer
183 views

MOOCs for Python in Data Science

Thanks also to SE, I've recently changed job and now I'm working in Data Science, mainly on Analytics for the IoT (Internet of Things). Analytics are applications on cloud platforms which collect real-...
1
vote
2answers
566 views

How to understand equations in research papers?

I was searching for latent class logit model for conjoint analysis. i found a paper which has equations for this model. I have co-workers who knows how to decipher the meaning of these equations and ...
1
vote
1answer
95 views

Questions regarding deep learning?

I have questions regarding this Normalized weights and Initial inputs video on Udacity course Deep Learning In this video the lecturer talks about variables that go into Big-loss function should have ...
1
vote
1answer
34 views

Book about distances for data science (can't remember the name)

I saw a book somewhere that listed a big amount of mathematical distance functions (the usual euclidean norms, the discrete distance, the hamming distance, etc) used for data science. The name of the ...
1
vote
1answer
43 views

How has data generation evolved over the years (and centuries)?

I would like to know how data generation has evolved through the years. My end goal would be to generate a logarithmic line plot showing the ridiculous increase in data generation. Please, does ...
1
vote
1answer
23 views

Voting patterns similarities

I'm interested in any research materials on voting patterns. I have a data set of how PMs (members of parliament) voted in my country during last couple of years. Each PM has 3 buttons: Yes, No, ...
1
vote
1answer
396 views

What are prototypes in RBF networks?

I am currently reading Boosting the Performance of RBF Networks with Dynamic Decay Adjustment by Michael R. Berthold and Jay Diamond (online) to understand how Dynamic Decay Adjustment (DDA; a ...
1
vote
1answer
36 views

What are the possible applications of a Data Scientist in the design fase of an Aerospace Or Railway Engineering industry? [closed]

I have been trying to understand this for a long time, but this information proves to be incredibly elusive online. What are possible jobs that a pure Data Scientist, without much background knowledge,...
1
vote
0answers
19 views

What are some good resources for setting up and debugging neural networks?

I am aware of Troubleshooting Deep Neural Networks by Josh Tobin and A Recipe for Training Neural Networks by Andrej Karpathy, but I am interested in other resources that can give me some guidelines ...