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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6 views

Find a specific paper on information retrieval method supporting literature research searching not by keywords but by documents

About 2012, I did a literature research on the following topic but unfortunately lost my results. Specifically one paper comes repeatedly to my mind, therefore maybe someone knows about this or ...
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1answer
33 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 The few I found are outdated.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?
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Research on explaining generalizability of deep learning methods

I've read a few classic papers on different architectures of deep CNNs used to solve varied image-related problems. I'm aware there's some paradox in how deep networks generalize well despite ...
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9 views

Print media (periodical) on Data Science?

My company is currently looking for classical periodicals on Data Science / Data / Machine Learning / Statistics / Deep Learning. Although there are plenty of online resources available, curated print ...
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4answers
245 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 ...
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1answer
36 views

How CNN applies backpropagation to update its weights and biases?

I understand that the 3 main layers for CNN are convolutional layer, ReLU layer and pooling layer. However, I do not understand how CNN updates its weights and biases using backpropagation. I ...
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1answer
18 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 ...
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29 views

Optimizing parameters for an image-generation algorithm

I have a program that takes an image and a list of parameters and generates a new image. I would like to automate the selection of parameters to produce the 'best' image. 'Best' in this context doesn'...
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1answer
20 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 ...
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1answer
50 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 ...
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12 views

Correlation between (average daily) impressions and user response ratio in social media

I'm doing a preliminary study on data from a (niche) social media platform. Studying the correlations between impressions of an object (aka views), interactions (aka likes, comments, ...) and their ...
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27 views

Reference for Inception-v2

The "Rethinking" paper doesn't describe the actual implementation of the Inception-v3 model in Tensorflow: an accurate description is written in model.txt in the source files of the paper in the arXiv....
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8 views

How do WordNet and GloVe relate?

Please help to disambiguate. Are these things actually comparable/relatable? Do both models contain similar sets of words? Is GloVe kind of more advanced WordNet due to measurable vector distances?
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1answer
54 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 ...
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27 views

Long range dependency dataset

I am doing a project concerning formal languages and I want to relate them to DL structures. In this regard, I am looking for datasets that include enough long-range dependency for the use of ...
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1answer
44 views

Protein interaction prediction- how to input this data structure

I know the basics of machine learning and have quite an experience with time series data or data fed in a tabular format. But in the picture, the data is arranged as a graph. Is there a way to input ...
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28 views

Recognition of objects in almost plain background

I want to recognize climbing holds in a climbing wall. I thought about implementing my own heuristic algorithm for background detection because it's almost plain, but I was wondering if this kind of ...
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1answer
107 views

What is the difference between market segmentation and customer segmentation?

Market segmentation seems to be the more widespread, both in books and on websites: What are the differences between market segmentation and customer segmentation? Both are basically about clustering ...
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1answer
36 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?
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1answer
28 views

algorithm to auto-download articles from the internet

I have an issued in my homeworks and I thinked if there is an rxisted algorithm or if can i create new one that takes key words like "germany" and "polution" and parses in google scholar. It parses ...
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2answers
100 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}=\{...
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15 views

Learning Attention Based Models [books]

Today I read an interesting post to drop RNNs for sequential models. However, the post, unfortunately, didn't go into much detail on how one would study the attention based models and start ...
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2answers
178 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? ...
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3answers
196 views

Forecast vs Prediction: What is the difference?

I use the two terms as follows: A prediction model gets features (which can be a time series) as input and gives a fixed-length output (might be multiple values, but "atomic" in some sense) Examples:...
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1answer
75 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 ...
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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, ...
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2answers
355 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 ...
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3answers
3k 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 ...
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2answers
141 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? ...
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0answers
127 views

ElasticSearch for data scientists [closed]

This is to seek career advice for a data scientist. What pertains within the role of data scientist and what does not regarding ElasticSearch. Does backend development for ElasticSearch using ...
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5answers
3k 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 ...
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0answers
24 views

Possibility of self-growing neural nets

What is the state of the art for DNNs to infer that they need more neurons than in the initial setup? Can they be acquired dynamically from the underlying "resource substrate"?
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1answer
29 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 ...
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1answer
49 views

Can you use machine learning to extract the entropy from a hand print reliably?

Let's say that I want to generate a cryptographic key based on my hand (I'm using hands just as an example). What I could do is I scan my hand (so that the friction ridges are apparent) and then use a ...
2
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2answers
54 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 ...
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1answer
155 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-...
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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 ...
6
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1answer
6k 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}...
2
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1answer
367 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 ...
4
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1answer
853 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.
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4answers
3k 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 ...
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2answers
352 views

OpenNLP tutorial or book

I am very new to Java and primarily a Python and R user. I want to use OpenNLP for certain NLP tasks that I have been entrusted with. Is there any good tutorial or book on OpenNLP that anyone can ...
3
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1answer
151 views

What does a professional DS stack look like? [closed]

I'm looking for resources that talk about best practices or simply some examples (at specific companies or in general) on how tech companies that heavily use machine learning like Twitter, Facebook ...
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3answers
2k 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 ...
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3answers
2k 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 ...
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8answers
13k 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 ...
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3answers
180 views

What are good films for teaching data-driven decision making? (like Moneyball)

What are good films for teaching data-driven decision making? In one of my classes, I asked my students to watch Moneyball at home and we discussed it in the class. It was successful and they learned ...
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2answers
172 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 ...
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2answers
158 views

How can one use unstructured data for forecasting?

How can one use unstructured data for forecasting purposes? (by unstructured, I mean unstructured in the database sense). I have a forecasting system that uses historical data and a set of ...
4
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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 ...