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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2
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1answer
35 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 ...
3
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1answer
31 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/...
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0answers
13 views

Reconstructing an audio signal from its Mel-scale spectrogram using an autoencoder

I'm looking for some papers/references that attempted to reconstruct audio signals from their Mel-scale spectrograms using an autoencoder or other neural network. I am thinking of training the ...
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0answers
5 views

Recommendations for notable papers/analyses that make use of 'big' spatial data?

This is a reference request. I am seeking papers that make use of 'big' (subjective) spatial datasets in their analyses. While I am open to machine learning papers, I am also interested in papers that ...
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0answers
30 views

Is there a pre-trained network trained on RGB-D (4) channels?

The most used pre-trained networks for computer vision (e.g. ResNet50) are trained on 3 channels (RGB). At the same time, many cameras used in robotics return RGB-D outputs, that is including depth ...
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0answers
16 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 ...
8
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1answer
278 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 ...
2
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0answers
44 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....
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0answers
24 views

Kernel approximation of a function known only point-wise?

Assume that I have a set of $N$ points $x_i, i=1,...,N,$ in some space $\mathbb{R}^D$, and corresponding point-wise (scalar) function evaluations $f(x_i)$. It is my goal to approximate the unknown ...
2
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0answers
69 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 ...
0
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1answer
33 views

Where to upload large (0.5Gb) weights anonymously?

I need to upload a number of checkpoints for ConvNets (weights + optimizers, all dicts of pytorch tensors), each about 0.5Gb anonymously. I don't want to use Google Drive. I trained models on the ...
3
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1answer
55 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 ...
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1answer
2k views

What is “lag” in time series forecasting?

I'm studying machine learning (e.i. time series analysis). I encountered an Azure tutorial, Retail Forecasting. https://gallery.azure.ai/Experiment/Retail-Forecasting-Step-2-of-6-train-time-series-...
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0answers
23 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 ...
1
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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?
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4answers
760 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 ...
0
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1answer
180 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 ...
1
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1answer
26 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
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1answer
34 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 ...
3
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2answers
452 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 ...
1
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0answers
13 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 ...
3
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1answer
702 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 ...
0
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1answer
55 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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0answers
47 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 ...
2
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1answer
158 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
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1answer
32 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 ...
4
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2answers
121 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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0answers
19 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 ...
7
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5answers
698 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
497 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:...
4
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1answer
111 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 ...
1
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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, ...
2
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2answers
522 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 ...
7
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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 ...
1
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2answers
161 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
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0answers
137 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 ...
16
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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 ...
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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"?
1
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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 ...
-2
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1answer
52 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
56 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
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1answer
180 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
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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 ...
8
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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}...
2
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1answer
402 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
1k 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
4k 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
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1answer
376 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 ...
17
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4answers
4k 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
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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 ...