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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.

0
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1answer
18 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 ...
0
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0answers
12 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 ...
-1
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1answer
23 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 ...
1
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1answer
11 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?
0
votes
1answer
22 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 ...
0
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0answers
47 views

Reinforcement learning using Restricted Boltzmann Machine(RBM)

I am very new to the field of machine learning, AI and related things. I am right now, in particular looking for some references where RBMs can be used to achieve Reinforcement learning, something ...
4
votes
2answers
80 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}=\{...
1
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0answers
9 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 ...
3
votes
2answers
65 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? ...
0
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3answers
151 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:...
3
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0answers
46 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 ...
0
votes
1answer
18 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, ...
2
votes
2answers
246 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 ...
3
votes
2answers
838 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 ...
0
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0answers
26 views

Training of neural nets as an optimization problem?

Please help me to find references on the following topic. Currently, a successful setup of a training of neural net seems a little bit like woodoo with lots of parameters. Like, volume and quality of ...
1
vote
0answers
103 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 ...
13
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5answers
2k views

Beginner math book for Machine Learning

I'm a Computer Science engineer with no background in Statistics nor in advanced math. I'm studying the book "Python Machine Learning" by Raschka and Mirjalili, but when I tried to understand the ...
1
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0answers
20 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"?
1
vote
1answer
24 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 ...
-2
votes
1answer
43 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
votes
2answers
51 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 ...
1
vote
1answer
126 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-...
4
votes
2answers
878 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
3k 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
votes
1answer
336 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 ...
3
votes
1answer
567 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.
6
votes
4answers
2k 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 ...
0
votes
1answer
295 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
votes
1answer
132 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 ...
6
votes
3answers
1k 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 ...
2
votes
3answers
991 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 ...
48
votes
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 ...
0
votes
3answers
143 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 ...
1
vote
2answers
108 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 ...
0
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2answers
130 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
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 ...
1
vote
1answer
84 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 ...
3
votes
1answer
845 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) = ...
1
vote
1answer
4k 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.
1
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1answer
4k views

Markov switching models

What are some reference sources for understanding Markov switching models?
0
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0answers
45 views

Support vector machines used for prime factorisation with polynomials?

Suppose a polynomial. Each monomial can be linked to other monomials in a number of ways. The distribution of degrees, centrality measures and order investigations with different bases like here may ...
1
vote
1answer
200 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
180 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 ...
16
votes
6answers
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) ...
6
votes
1answer
525 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 ...
4
votes
4answers
124 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 '...
1
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0answers
67 views

Does anyone have any thought how come the fuzzy rules can be verified and validated?

Fuzzy logic was utilized to derive a performance indicator of some manufacturing facilities in an uncertain environment. There are some historical data obtained from some manufacturing facilities’ ...
9
votes
3answers
5k 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,...
4
votes
1answer
2k 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 "...
3
votes
4answers
5k views

Resources on Data Science for Football / Soccer?

I am searching for resources on data science projects which used football/soccer data.