Questions tagged [self-study]

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Recommendations for Master courses in Data Science in Europe

I am hoping somebody can help a (hopefully) future data scientist: I am looking for a Master course in data science at a school in Europe. I have a Bachelor in Media Management (PR & Communication)...
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6 answers
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Machine Learning resources

I'm not sure if this is the right place to ask this question, but is there any online source that provides a complete in-depth explanation of Machine Learning algorithms, all at one place, but not too ...
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global contrast normalization implementation

I'm trying to understand figure 12.1 in Goodfellow available here. I'm not able to reproduce figure 12.1, and I'm wondering what is it I'm missing. The denominator of equation 12.3 is a constant, and ...
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2 votes
1 answer
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Resources on on-line machine learning

I am wondering if there are any books/articles/tutorials about "on-line machine learning"? For example, this website has nice lecture notes (from lec16) on some of the aspects: https://web....
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1 vote
2 answers
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Where can I find study materials? [closed]

Can anyone recommend me some material (books, blogs, youtube channels, ...) to study statistics, Machine Learning and in general Data Science topics? Thanks
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1 answer
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Studying and choosing between different neural network structures

I would like to develop a model that uses convolutional neural networks for image classification. From the many different network structures described in papers and articles online, I would like to ...
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1 vote
3 answers
195 views

Feeling Stuck on a Beginner – Intermediate level [closed]

Over the past two years, I have been working as a full-time data scientist for a government company. As the sole data science team in the organization, our job is a hybrid between data science and ...
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How to make a linear model with a constant value in R?

I'm working on an unassessed homework problem from unpublished course notes of a statistics module from a second year university mathematics course. I'm trying to plot a 2-parameter full linear model ...
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What ML techniques work on imbalanced datasets

I have some specific questions for which I could not find answers in textbooks/research articles. Shall be grateful for an answer. These are: Are there ML techniques that can be directly applied on ...
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1 answer
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Resampling : My dataset is categorical or numerical?

I have a dataset with 203 variables. Like age>40 (0 -yes, 1-no), gender(0 or 1), used or not 200 types of drugs (one hot encoded into 200 variables), and one target variable (0 or 1). This is an ...
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Logic behind the Statement on Non-Parametric models

I am currently reading 'Mastering Machine Learning with scikit-learn', 2E, by Packt. In Lazy Learning and Non-Parametric models topic in Chapter 3- Classification and Regression with k-Nearest ...
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1 answer
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Oracle in optimization

I have encountered the word oracle in the following context: Given an $\alpha$-approximate oracle for stochastic optimization we show how to implement an $\alpha$-approximate solution for robust ...
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Understanding SVM Kernels

Following Andrew Ng's machine learning course, he explains SVM kernels by manually selecting 3 landmarks and defining 3 gaussian function based on them. Then he says that we are actually defining 3 ...
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6 votes
2 answers
109 views

How do I test a difference between two proportions representing fatality rate for Covid 19 in Philippines and World (except Philippines)?

I'm trying to analyse if the fatality rate from my country (A third world country) vary significantly from the world's fatality rate. So I'd basically have two samples, labeled (Philippines) and (...
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1 vote
1 answer
179 views

Fastest way to relearn machine/deep learning

I hope I came to the right place to ask this question. Back when I was at collage I studied machine and deep learning in-depth. My whole programme was based on those areas. I knew all underlying ...
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2 votes
0 answers
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Four parameter self-starting function based on SSfpl

I am currently working with a self-starting function for four parameters which I based on SSfpl but with a different formula. This is the formula for my self-starting function: ...
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1 answer
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Analysis for basic weight training analysis?

TL;DR: I'm doing a fairly basic project which involves exercise. It seems that descriptive statistics and basic data vis (ex: line graph) would be most appropriate for this project, but I wonder if ...
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0 votes
1 answer
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Appraise the statement: “For the model 𝑦 = 𝛽0 + 𝛽1𝑥 + 𝑒, 𝛽1 reflects the causal effect of 𝑥 on 𝑦.” Ask

not sure if this was the right place to ask my question, but I saw some questions regarding linear regression so I'd thought I would try to get some answers here. I just started learning about linear ...
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1 answer
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Confusion regarding the Working mechanism of Activation function

For binary classification irrespective of the model used, the sigmoid function is a good choice for output layer because the actual output value ‘Y’ is either 0 or 1 so it makes sense for predicted ...
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2 answers
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Random Forest Techniques/Models

Can anyone tell about different Techniques/algorithms of Random forest? I know, Random Forest is itself an algorithm/model, but I'm looking for another version of it as we have in decision trees. List ...
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1 vote
1 answer
191 views

Efficient self study plan

I am hoping for a bit of guidance from experienced practitioners / academics. I want to work through the Bishop ML book, but have minimal background. What is the fastest way to get the pre-...
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6 votes
3 answers
5k views

What are some good books on Machine Learning and AI like Krugman, Wells and Graddy's "Essentials of Economics"

I am a Logistics student. I like the book "Essentials of Economics" by Krugman, Wells and Graddy in that it is concise, easygoing and not only a beginners book (it gradually approaches advanced ...
2 votes
1 answer
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Compute specificity and sensitivity at certain thresholds

I have the following table with predictive probabilities and true class labels: \begin{array}{|c|c|c|c|} \hline P(T=1) &0.54& 0.23 & 0.78 & 0.88 & 0.26 & 0.41 & 0.90 & ...
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Big data online class [closed]

Being an IT engineer, I am exploring the Big Data specialization and wishing to earn a certificate in that field to help me get a new job later. I've been looking around and found these two ...
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0 answers
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Is Chi Square goodness parametric or non-parametric? [closed]

Does Chi Square goodness of fit require normality assumption? Is it a parameteric or non-parametric test? What it its relation with t-test (parametric test) and u-test (non-parametric test)?
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1 answer
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Example data source for educaional use

I'm doing project on subject of affinity analysis for my statistical class in college. In order to complete it, I have to acquire sales database with at least 200-300 records, each containing list ...
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2 votes
1 answer
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Stacking LSTM layers

Can someone please tell me the difference between those stacked LSTM layers? First image is given in this question and second image is given in this article. So far what I learned about stacking LSTM ...
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4 votes
2 answers
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Depth of a Neural network

I was self-teaching myself. I totally understand why depth of a neural network affects the learning and how it differs than its width. But I am looking for some theoretical justification about it. ...
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2 votes
2 answers
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Conceptual question on CNN and any multi layer neural network (Part 2)

I have read a number of tutorials and online lectures (https://ujjwalkarn.me/2016/08/11/intuitive-explanation-convnets/) but none of them mention the rationale for selecting a particular design. How ...
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2 answers
367 views

Is ensemble learning using different classifier combination another name for Boosting?

For implementation I am following the Matlab code for AdaBoost. Based on my understanding, AdaBoost uses weak classifiers known as base classifiers and creates several instances of it. For example, a ...
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4 votes
2 answers
556 views

How to make sense of confusion matrix

Consider a binary classification problem with 0 labels denoting normal and 1 abnormal or rare. The number of instances with <...
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2 votes
1 answer
363 views

recommendations for self-study in ML/Deep Learning/the underlying math

I am a beginner in ML, though I have completed Andrew Ng's Machine Learning course on Coursera and am soon to complete his Deep Learning specialization, also on Coursera. I'm looking for ...
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0 answers
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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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0 votes
1 answer
41 views

Situations where advanced theoretical knowledge of ML helped solve a real world problem?

I've invested lot of time trying to understand the theoretical aspects of Deep Learning and Neural Networks - but I'm now questioning whether it is worth it or not, given that I am someone who works ...
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0 votes
1 answer
3k views

How Natural language processing and elasticsearch are related

I got call from a recruiter for an elasticsearch job. I am not sure how these 2 are related. Can anyone suggest and provide example use case?
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5 votes
1 answer
221 views

Early stopping and bounds

Say I am training neural networks using a train set and set aside a validation set V. I obtain models h's after each epoch along with the validation losses(0-1 loss) $\hat{L}(h_1,V)$, $\hat{L}(h_2,V)$ ...
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0 answers
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What would you recommend to know before considering applying for a master in Machine Learning?

As someone who is about to finish a bachelor in Software Engineering still learning the basics of machine learning but would like to enroll in a master's course focused on machine learning. What ...
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11 votes
1 answer
11k views

Gradient Boosting Tree: "the more variable the better"?

From the tutorial of the XGBoost, I think when each tree grows, all the variables are scanned to be selected to split nodes, and the one with the maximum gain split will be chosen. So my question is ...
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7 votes
5 answers
2k views

Does ensemble (bagging, boosting, stacking, etc) always at least increase performance?

Ensembling is getting more and more popular. I understand that there are in general three big fields of ensembling, bagging, boosting and stacking. My question is that does the ensembling always at ...
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1 vote
1 answer
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Analysis of railway data - Detecting outliers

I would like some pointers about the following problem: I would like to detect anomalies in a pretty huge collection of railway data. Or create a baseline model for detecting future anomalies. The ...
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6 votes
2 answers
5k views

What is init_score in lightGBM?

In the tutorial boosting from existing prediction in lightGBM R, there is a init_score parameter in function setinfo. I am ...
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0 votes
1 answer
387 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 ...
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0 votes
1 answer
102 views

What is the best tutorial to quickly learning machine learning in R [closed]

I want to learn machine learning methods, preferably high-performance methods, by R in the quickest way possible. I am totally familiar with R but very less experience with ML packages. I know some ...
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1 vote
1 answer
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Topics to cover for software developer interested in data analytics

First of all I don't know if this is the appropriate place to post this question. If it's not, I apologize in advance. It seems like the most relevant Stack Exchange sub. A little about myself: I'm ...
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1 vote
2 answers
697 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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16 votes
3 answers
5k views

How to self-learn data science? [closed]

I am a self-taught web developer and am interested in teaching myself data science, but I'm unsure of how to begin. In particular, I'm wondering: What fields are there within data science? (e.g., ...
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1 vote
0 answers
235 views

Binary classification with unexplained data

My apologies for cross-posting to stackoverflow and cross validated. Not really sure which one is the most relevant place. Please shed some light on me with this task. Description Assuming the ...
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6 votes
4 answers
10k views

What courses / subjects are most important to the field of Data Science?

I've taken it upon myself to begin a career change. I have a decent background in mathematics, but lack in programming or data science specific skills (such as data munging). I have been looking ...
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9 votes
2 answers
517 views

Relationship between VC dimension and degrees of freedom

I'm studying machine learning and I feel there is a strong relationship between the concept of VC dimension and the more classical (statistical) concept of degrees of freedom. Can anyone explain such ...
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2 votes
1 answer
232 views

Learning resources for Data Science for applications in road traffic data? [closed]

My Background I am a graduate student in Civil Engineering. For the analyses of road traffic data (vehicle trajectories as time series) I work with big data sets mostly about a million data points or ...
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