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H: problem with regular expression
I have a dataframe in R containing a variable for programming languages. This is extracted from a multiple choice questionnaire in a survey. As a result, any programming language may fall into the beginning, middle or end of the whole string.
I added a binary variable for any progra... |
H: Is SuperLearning actually different to stacking,or are they essentially the same thing?
Articles which use the terms 'stacking' and 'Super Learner' often seem to use the terms interchangeably. Is the Super Learner algorithm a specific form of the more generic stacking concept, or is Super Learner essentially the sa... |
H: How do I determine the best statistical way for data transformation for standardization (like log, sq root) to remove bias between different datasets?
I'm currently working on applying data science to High Performance Computing cluster, by analyzing the log files generated and trying to see if there is a pattern th... |
H: Does batch_size in Keras have any effects in results' quality?
I am about to train a big LSTM network with 2-3 million articles and am struggling with Memory Errors (I use AWS EC2 g2x2large).
I found out that one solution is to reduce the batch_size. However, I am not sure if this parameter is only related to memor... |
H: How to optimize cohort sizes to reduce pair-wise comparisons?
I am making all pairwise comparisons in a dataset. The use-case is collapsing records into a unique ID based on fuzzy names and dates of birth. The size of the database is around 57,000 individuals. So this is a total of 57,000 choose 2 pairwise combinat... |
H: Gaussian Mixture Models EM algorithm use average log likelihood to test convergence
I was investigating scikit-learn's implementation of the EM algorithm for fitting Gaussian Mixture Models and I was wondering how they did come up with using the average log likelihood instead of the sum of the log likelihoods to te... |
H: Multiclass Classification with large number of categories
I am making a recommendation system (kind of) and I have to recommend the item a user is most likely to buy in his next purchase. Doesn't matter if he already bought this item.
Given this, I'm treating this problem as a multiclass-classification problem with... |
H: Beginner in programming and data science with 100 hours to spend learning the basics
I started using the below link to teach myself data science, with some mathematical knowledge (including calculus, linear algebra, stats/probability) but very little programming experience:
Quora - Roman Trusov's answer on how to l... |
H: Measuring Value in Data Science?
Why does it seem that it's difficult to find out how people in data science create measurable value? All I find on the internet are buzzwords like data cleaning, visualization, and writing about the data. This is equivalent of describing a landscaper as trimming trees and grass or... |
H: "Results do not have equal lengths" using ldply in R package plyr
I've found a few similar questions, but I am new to R and can't figure out how it applies to my specific problem. Here is my code:
library(rvest)
library(plyr)
library(stringr)
#function passes in letter and extracts bold text from each page
fetch_c... |
H: Similarity between two words
I'm looking for a Python library that helps me identify the similarity between two words or sentences.
I will be doing Audio to Text conversion which will result in an English dictionary or non dictionary word(s) ( This could be a Person or Company name) After that, I need to compare i... |
H: Can we use a model that overfits?
I am on a binary classification problem with the AUC metrics. I did a random split 70%, 30% for training and test sets.
My first attempts using random forest with default hyper-parameters gave me auc 0.85 on test set and 0.96 on training set.
So, the model overfits. But the score ... |
H: Understanding Bernoulli Trials, Bayesian Setting
I am required to complete a project on ML applications. I guess there is a lot of statistics in ML, not helpful for a non-maths background.
I am getting too bogged down by notations. There are too many notations.
I am trying to read about what Bernoulli trials are a... |
H: Smith-Waterman-Gotoh Algorithm - how to determine an overall similarity percentage
Using the Smith-Waterman-Gotoh algorithm I want to get an overall similarity percentage between two sequences. What would be the best way to do this?
eg. comparing strings COELACANTH and PELICAN in this example gives a score of 4 wi... |
H: How to count the number of missing values in each row in Pandas dataframe?
How can I get the number of missing value in each row in Pandas dataframe.
I would like to split dataframe to different dataframes which have same number of missing values in each row.
Any suggestion?
AI: You can apply a count over the rows ... |
H: How does SelectKBest() perform feature selection?
SelectKBest(f_classif, k), where k is the number of features to select, is often used for feature selection, however, I am having trouble finding descriptive documentation on how it works. A sample of how this works is below:
model = SelectKBest(f_classif, k)
model... |
H: How to take advantage of variables whose values are available in the past but not in the future?
Example: weather data. You know the location data, but you don't know the previous days'/weeks' temperatures and other weather conditions. How can you exploit these variables in your past data when you build a predictiv... |
H: word2vec -storing a word and its vector yet be able to efficiently run k-nearest neighbour
After training a model using word2vec I'd now like to store the trained model with the word serving as a key and the vector as its value. However I'm not sure how I'll be able to implement in this way a k-nearest neighbour se... |
H: Date prediction - periodic recurrence
If I have some data regarding the occurence of an event on a certain date and some other variables regarding it (think fe.: I have data on which dates it rained, and some addtitional data like temperature, atmospheric pressure etc.), which is the most appropriate model for pred... |
H: How to decide power of independent variables in case of non-linear polynomial regression?
Consider one dependent variable 'Y' and 10 independent variables or features- X1, X2, X3, ... X10.
I want to create a non-linear polynomial regression model such that-
Y ~ a1.X1^b1 + a2.X2^b2 + .... + a10.X10^b10
I was wonderi... |
H: Where does the random in Random Forests come from?
As the title says:
Where does the random in Random Forests come from?
AI: For each tree you randomly select from the variables that you can use to split tree nodes. Generally you randomly select 1/3 of the variables per tree. |
H: What is the definition of precision for no positive classifications?
The precision is defined as
$$\text{precision} = \frac{\text{true positive}}{\text{true positive} + \text{false positive}}$$
Is there any definition what this value should be if there is no positive classification (but of course positive elements... |
H: Tools for ML on csv files and jsons
So much of what we export is in CSV and JSON files.
Is there any useful tools you know of that can automatically perform data analysis on flat file formats. For example
Basic statistics if numeric types: avg, stdev, mode, median
Column type and Cardinality detection
Find relati... |
H: How to architect ConvNet to ignore top half of image
I'm building a convoluted neural network to teach a toy car, powered by a Raspberry Pi, how to drive based on incoming streams of frames from a webcam mounted on top of the car. The top half of each image is irrelevant. What matters is the curvature of the road, ... |
H: Should we convert independent continous variables (features) to categorical variable before using decision tree like classifier?
Consider I have one dependent variable to predict 'Attitude' which can take three values 'Positive/Negative/Neutral'.
I have following independent variables or features- Age, Height, Gend... |
H: Why are sigmoid/tanh activation function still used for deep NN when we have ReLU?
Looks like ReLU is better then sigmoid or tanh for deep neural networks from all aspects:
simple
more biologically plausible
no gradient to vanish
better performance
sparsity
And I see only one advantage of sigmoid/tanh: they are b... |
H: DIfferent learning rates converging to same minima
I am optimizing some loss function using Gradient Descent method. I am trying it with different learning rates, but the objective function's value is converging to same exact point.
Does this means that I am getting stuck in a local minima?, because the loss funct... |
H: Machine Learning Identification and Classification, based on string contents: General advice
I have just very recently started to develop an interest in machine learning, and I have a particular problem in mind that I would like to start to explore.
I would like to train a system to automatically classify various a... |
H: Minimize absolute values of errors instead of squares
Calculating absolute values is much more efficient than calculating squares. Is there any advantage, then, to using the latter as a cost function over the former? Squares are easier to treat analytically, but in practice that doesn't matter.
AI: In what term "ca... |
H: Backpropagation: In second-order methods, would ReLU derivative be 0? and what its effect on training?
ReLU is an activation function defined as $h = \max(0, a)$ where $a = Wx + b$.
Normally, we train neural networks with first-order methods such as SGD, Adam, RMSprop, Adadelta, or Adagrad. Backpropagation in first... |
H: r - How to determine the correlation between unordered categorical variables and individuals?
I have a matrix with several unordered categorical variables. Each row represents a type of individual. Each column represents the number of times each type of individual was found to be in that particular condition.
Type ... |
H: LSTMs: what is $W_x$ & $U_z$ in $φ(W_x + U_z + b)$?
Reading On Multiplicative Integration with Recurrent Neural Networks
Despite of their varying characteristics, most of them(RNNs) share a common
computational building block, described by the following equation:
$φ(W_x + U_z + b)$, where $x ∈ R_n$ and $z ∈ R_... |
H: Should a model be re-trained if new observations are available?
So, I have not been able to find any literature on this subject but it seems like something worth giving a thought:
What are the best practices in model training and optimization if new observations are available?
Is there any way to determine the per... |
H: location of the resampled data from SMOTE
I am using SMOTE in Python to perform oversampling of the minor class in an unbalanced dataset. I would like to know the way SMOTE formats its output, that is, whether SMOTE concatenates the newly generated samples to the end of the input data and returns that as the output... |
H: Where can I find a software library for pairwise matching (ideally, Python, R, Java)?
I am looking for a library that implements a pairwise ranking algorithm. For example, if I have 200 writing samples from 100 people (two samples from each individual) and I want to identify which samples belong together (i.e., wer... |
H: Is there an R package which uses neural networks to explicitly model count data?
Ripley's nnet package, for example, allows you to model count data using a multi nomial setting but is there a package which preserves the complete information relating to a count?
For example, whereas an ordinal multinomial model pres... |
H: Correlating company entities between different data sources
I have two datasets with information about companies and my task is to correlate (match) companies from dataset A to companies in dataset B. Datasets are from different sources.
The columns in both datasets include fields such as company_name, country, sta... |
H: Sklearn feature selection stopping criterion (SelectFromModel)
Sklearn has several functions for feature selection that lets the user determine the size of the chosen subset. An example of this is SelectKBest where the user determines the value of "k", which is the number of top performing features.
Does anyone kno... |
H: Using RNN (LSTM) for predicting one future value of a time series
I have been reading several papers, articles and blog posts about RNNs (LSTM specifically) and how we can use them to do time series prediction. In almost all examples and codes I have found, the problem is defined as finding the next x values of a t... |
H: What does normalizing and mean centering data do?
Are there any concerns to normalizing data to be within the range 0 - 1 and mean centering the data as well?
Does it matter which comes first?
If you do one, is the other not required?
AI: If you don't center before you normalize, you don't take advantage of the fu... |
H: Deep learning - rule generation
I wanted to know if there is any methodology in Deep/Machine learning, where given a set of input/output values, it can derive rules for the same.
Lets say I generate training input and output by $y=x^2$
i/p | o/p
0 0
2 4
. .
1000 1000000
It sort of generate... |
H: Represent outlier days
I have hourly power consumption data for 30 days. On representing, each day data using a separate line, I get a plot as
I want to highlight the days with abnormally high consumption (in other words, the outlier days). I think that the current plot is too much congested. Is there any other be... |
H: how to generate sample dataset for classification problem
I am a newbie to data science. I have a 'short text' categorization problem where input variables are either unstructured texts (names, definition, description etc) or categorical. There is not much semantic to the fields as they are product names, territory... |
H: How are 1x1 convolutions the same as a fully connected layer?
I recently read Yan LeCuns comment on 1x1 convolutions:
In Convolutional Nets, there is no such thing as "fully-connected layers". There are only convolution layers with 1x1 convolution kernels and a full connection table.
It's a too-rarely-understood f... |
H: Predicting Age of Birth
I have a pet project to figure out the birth year of a significant person in history.
I'm collecting a lot of data on other people with similar status during that time period. I have data such as education length, year married, year of child bearing, information about siblings and age diffe... |
H: Prediction with non-scalar output (label)
I have recently confronted with a (at least for me) new kind of ML problem, where the output of the model should be a vector/matrix (depending on the interpretation, but there is no difference actually), not a scalar as usual. This is totally unknown for me. What kind of ap... |
H: What is the simplest neural network for the simplest nonlinear function $f(x,y) =xy$
How do I capture $y = x_1 x_2$ using a simple neural network with commonly used activation functions? I assume that I need at least one hidden layer. What mix of commonly activation functions should I use?
So far, I have used $max(... |
H: How to handle the CEO expectations from a company that's new to data science?
I'm new here. I'm about to have a final interview for a data scientist position for a company (it's in the e-commerce field) that is new for data science. It's a pretty new position for the company, and from the interviews I had so far, I... |
H: recommendation system for eCommerce healthcare portal suggestion
I am trying to build a recommendation system. My system is basically a ecommerce application where our customers answers a bunch of questions related to healthcare (their basic health related question). Based on their ansers, we recommend some product... |
H: Is TensorFlow a complete Machine Learning Library?
I am new to TensorFlow and I need to understand the capabilities and shortcomings of TensorFlow before I can use it. I know that it is a deep learning framework, but apart from that which other machine learning algorithms can we use with tensor flow. For example ca... |
H: Choosing the right parameters to train a Tf-Idf vectoriser
I'm very new to the DS world, so please bear with my ignorance.
I'm trying to analyse user comments in Spanish. I have a somewhat small dataset (in the 100k's -- is that small?), and when I run the algorithm in a, let's say, naïve way (scikit-learn's defaul... |
H: Scikit Learn OneHotEncoded Features causing error in classifier
I’m trying to prepare data for input to a Decision Tree and Multinomial Naïve Bayes Classifier.
This is what my data looks like (pandas dataframe):
Label Feat1 Feat2 Feat3 Feat4
0 1 3 2 1
1 0 1 1 2
2 ... |
H: Is it possible to (de)activate a specific set of cells in jupyter?
I have a jupyter notebook and I would like to perform several runs, the code I want to run depending on the results of the previous runs. I divided my notebook into several cells, and for each run I would like to select which cell should be executed... |
H: statistics or robust statistics for identifying multivariate outliers
For the single variate data sets, we can use some straightforward methods, such as box plot or [5%, 95%] quantile to identify outliers. For multivariate data sets, are there any statistics that can be used to identify outliers?
AI: Multivariate o... |
H: Should I use regularization every time?
I have learned regularization for linear and logistic regression but when I implement that algorithm to my code generally my estimates not changing.I mean,it looks like ineffective.I know,it's for overfitting.So if I use it in my code every time ,could it be a problem? or is ... |
H: Is there an open source implementation for bag-of-visual words?
I'm not quite sure I understand the bag-of-visual-words representation, so I may misformulate my question.
What I'm currently looking for is an open source library (possibly with python API). I give it pictures as input, and its output is a set of (spa... |
H: From developper to data scientist
I code a lot for web, games and some basic ML scripts. Now I would like to learn about data science.
This post is a good starting point but I would like some readings. I would like advices on books for a beginner (maths, tools, whatever).
I've found these ones from O'Reilly :
Mac... |
H: Merging large CSV files in pandas
I have two CSV files (each of the file size is in GBs) which I am trying to merge, but every time I do that, my computer hangs. Is there no way to merge them in chunks in pandas itself?
AI: No, there is not. You will have to use an alternative tool like dask, drill, spark, or a goo... |
H: Replacing column values in pandas
I have a data frame which has three columns as shown below. There are about 10,000 entries in the data frame and there are duplicates as well.
Hospital_ID District_ID Employee
Hospital 1 District 19 5
Hospital 1 District 19 10
Hospital 1 District 19 6
Hospital 2 ... |
H: To learn machine learning which one is good?
Until now I have implemented linear and logistic regression myself. I have not used any library other than numpy and matplotlib. But in the internet every example is solved using libraries such as sklearn, pandas and etc. My question is, which one is good to learn for ma... |
H: Is t-SNE just for visualization?
I have used the t-SNE algorithm to visualize my high dimensional data. However, I was wondering if this is a practical method for inference?
AI: It's a dimensionality reduction algorithm. Inference is the problem of determining the parameters, or labels, that best fit the model for ... |
H: String Values in a data frame in Pandas
Suppose I have a data frame like this :
Hospital_name State Employees ......
Fortis Delhi 5000 ......
AIIMS Delhi 1000000 ......
SuperSpeciality Chennai 1000 ......
Now I want to use this data frame to build a machin... |
H: Looking for an algorithm that correctly clusters visually separable clusters
I have visualized a dataset in 2D after employing PCA. As 2D visualization shows in figure, there is a good separation between points (A, B). Now, I want to use a metric which can separate these points (between these 2 PC components not in... |
H: How to further improve the kaggle titanic submission accuracy?
I am working on the Titanic dataset. So far my submission has 0.78 score using soft majority voting with logistic regression and random forest. As for the features, I used Pclass, Age, SibSp, Parch, Fare, Sex, Embarked.
My question is how to further boo... |
H: Depending upon how I download, I get two different files
I am downloading the data set for the Kaggle competition on the titanic.
If I use the following code :
if (!file.exists("data")){
dir.create("data")
}
fileUrl <- 'https://www.kaggle.com/c/titanic/download/train.csv'
download.file(fileUrl, destfile='./data/... |
H: MLP on Iris Data not working but it does fine on MNIST - Keras
So I'm a little bit baffled. I have just started working with the Keras framework for Python (which is awesome by the way!).
However just trying a few simple test of neural networks has got me a bit confused. I initially tried to classify the Iris data ... |
H: How do I factor in features which are IDs?
I am an absolute beginner in data science and I had this (possibly stupid) question on my mind, while reading a problem in Kaggle: Say I'm given IDs of some clients, IDs of products that they sell, and quantity of the product sold, and I'm asked to predict the quantity of ... |
H: What is the difference between word-based and char-based text generation RNNs?
While reading about text generation with Recurrent Neural Networks I noticed that some examples were implemented to generate text word by word and others character by character without actually stating why.
So, what is the difference bet... |
H: K-means Clustering algorithm problems
I am trying to implement k-means clustering algorithm, but I am confused about calculating the distance and update(move) cluster centroids. For example, let's say that I have 2 features. One of them is weight={2,4,6,8,11,14,21} and the other one is height={4,6,7,8,9,12,14}. So,... |
H: One-hot encoding
I am going through tensor-flow tutorial and noticed that they use one-hot encoding in regression tensorflow. I don't fully understand how it works. Let us take oversimplified case of ordinary least square regression. Assume we have y = [1,2,3] and x = [cat, dog, mouse]. Converting to one hot vector... |
H: Different runs of feature selection algorithm giving different set of selected feature. How to choose the best set among them?
I am using the forward feature selection algorithm from MATLAB. The code is as follows:
X=combine_6_non;
y=target;
c = cvpartition(y,'k',10);
opts = statset('display','iter');
[fs,hist... |
H: Are there pitfalls in using the output of machine learning model, such as a neural net as the input to a traditional GLM or similar?
To be more specific, loss reserving models in actuarial science, such as the chain ladder method, can be expressed as GLMs. I have developed a predictive model using neural nets which... |
H: Which features can help to differentiate these two density?
I'm wondering that is there any features that can help in differentiating the following two images. I mean differentiating in related numbers.
AI: Regarding two probability distributions $A,B$ on the line, that have densities, the following are equivalent:... |
H: How do companies like Amazon track what products are most frequently bought together?
What methods could someone use to find out what products are most frequently grouped with each other per order? Are there applications that can make achieving this goal easier?
AI: This is called Association Learning. Quoting Wikp... |
H: Using Decision Tree methodology to identify Independent Variables for Multiple Regression
Have access to a dataset with hundreds of variables and millions of cases (American Community Survey).
Need to identify a small, manageable set of Independent Variables (IVs) to use for Multiple Regression.
One way to do this,... |
H: Is there a problem of over fitting in my dataset?
I have applied the sequential forward selection to my dataset having 214 samples and 515 features (2 class problem). The feature selection algorithm has selected 8 features. Now I have applied the svm (MATLAB) on these 8 features. I have also tried to see the perfor... |
H: What open-source books (or other materials) provide a relatively thorough overview of data science?
As a researcher and instructor, I'm looking for open-source books (or similar materials) that provide a relatively thorough overview of data science from an applied perspective. To be clear, I'm especially interested... |
H: K-Means clustering for mixed numeric and categorical data
My data set contains a number of numeric attributes and one categorical.
Say, NumericAttr1, NumericAttr2, ..., NumericAttrN, CategoricalAttr,
where CategoricalAttr takes one of three possible values: CategoricalAttrValue1, CategoricalAttrValue2 or Categorica... |
H: The data in our relational DBMS is getting big, is it the time to move to NoSQL?
We created a social network application for eLearning purposes. It's an experimental project that we are researching on in our lab. It has been used in some case studies for a while and the data in our relational DBMS (SQL Server 2008)... |
H: Is Data Science the Same as Data Mining?
I am sure data science as will be discussed in this forum has several synonyms or at least related fields where large data is analyzed.
My particular question is in regards to Data Mining. I took a graduate class in Data Mining a few years back. What are the differences be... |
H: How big is big data?
Lots of people use the term big data in a rather commercial way, as a means of indicating that large datasets are involved in the computation, and therefore potential solutions must have good performance. Of course, big data always carry associated terms, like scalability and efficiency, but wh... |
H: What is the difference between Hadoop and noSQL
I heard about many tools / frameworks for helping people to process their data (big data environment).
One is called Hadoop and the other is the noSQL concept. What is the difference in point of processing?
Are they complementary?
AI: Hadoop is not a database, hadoo... |
H: Is the R language suitable for Big Data
R has many libraries which are aimed at Data Analysis (e.g. JAGS, BUGS, ARULES etc..), and is mentioned in popular textbooks such as: J.Krusche, Doing Bayesian Data Analysis; B.Lantz, "Machine Learning with R".
I've seen a guideline of 5TB for a dataset to be considered as Bi... |
H: Use liblinear on big data for semantic analysis
I use Libsvm to train data and predict classification on semantic analysis problem. But it has a performance issue on large-scale data, because semantic analysis concerns n-dimension problem.
Last year, Liblinear was release, and it can solve performance bottleneck.
B... |
H: Running an R script programmatically
I have an R script that generates a report based on the current contents of a database. This database is constantly in flux with records being added/deleted many times each day. How can I ask my computer to run this every night at 4 am so that I have an up to date report waiting... |
H: Why Is Overfitting Bad in Machine Learning?
Logic often states that by overfitting a model, its capacity to generalize is limited, though this might only mean that overfitting stops a model from improving after a certain complexity. Does overfitting cause models to become worse regardless of the complexity of data,... |
H: Clustering customer data stored in ElasticSearch
I have a bunch of customer profiles stored in a elasticsearch cluster. These profiles are now used for creation of target groups for our email subscriptions.
Target groups are now formed manually using elasticsearch faceted search capabilities (like get all male cu... |
H: Is there a replacement for small p-values in big data?
If small p-values are plentiful in big data, what is a comparable replacement for p-values in data with million of samples?
AI: There is no replacement in the strict sense of the word. Instead you should look at other measures.
The other measures you look at d... |
H: Parallel and distributed computing
What is(are) the difference(s) between parallel and distributed computing? When it comes to scalability and efficiency, it is very common to see solutions dealing with computations in clusters of machines, and sometimes it is referred to as a parallel processing, or as distributed... |
H: When are p-values deceptive?
What are the data conditions that we should watch out for, where p-values may not be the best way of deciding statistical significance? Are there specific problem types that fall into this category?
AI: You are asking about Data Dredging, which is what happens when testing a very large... |
H: Is this Neo4j comparison to RDBMS execution time correct?
Background: Following is from the book Graph Databases, which covers a performance test mentioned in the book Neo4j in Action:
Relationships in a graph naturally form paths. Querying, or
traversing, the graph involves following paths. Because of the
fun... |
H: How does a query into a huge database return with negligible latency?
For example, when searching something in Google, results return nigh-instantly.
I understand that Google sorts and indexes pages with algorithms etc., but I imagine it infeasible for the results of every single possible query to be indexed (and r... |
H: Does click frequency account for relevance?
While building a rank, say for a search engine, or a recommendation system, is it valid to rely on click frequency to determine the relevance of an entry?
AI: Depends on the user's intent, for starters.
Users normally only view the first set of links, which means that un... |
H: Clustering unique visitors by useragent, ip, session_id
Given website access data in the form session_id, ip, user_agent, and optionally timestamp, following the conditions below, how would you best cluster the sessions into unique visitors?
session_id: is an id given to every new visitor. It does not expire, howev... |
H: What is the Best NoSQL backend for a mobile game
What is the best noSQL backend to use for a mobile game? Users can make a lot of servers requests, it needs also to retrieve users' historical records (like app purchasing) and analytics of usage behavior.
AI: Some factors you might consider:
Developer familiarity: g... |
H: Machine learning techniques for estimating users' age based on Facebook sites they like
I have a database from my Facebook application and I am trying to use machine learning to estimate users' age based on what Facebook sites they like.
There are three crucial characteristics of my database:
the age distribution ... |
H: When a relational database has better performance than a no relational
When a relational database, like MySQL, has better performance than a no relational, like MongoDB?
I saw a question on Quora other day, about why Quora still uses MySQL as their backend, and that their performance is still good.
AI: It depends o... |
H: How to learn noSQL databases and how to know when SQL or noSQL is better
I want learn about NoSQL and when is better to use SQL or NoSQL. I know that this question depends on the case, but I'm asking for a good documentation on NoSQL, and some explanation of when is better to use SQL or NoSQL (use cases, etc). Also... |
H: What is dimensionality reduction? What is the difference between feature selection and extraction?
From wikipedia:
dimensionality reduction or dimension reduction is the process of
reducing the number of random variables under consideration, and
can be divided into feature selection and feature extraction.
What i... |
H: Publicly Available Datasets
One of the common problems in data science is gathering data from various sources in a somehow cleaned (semi-structured) format and combining metrics from various sources for making a higher level analysis. Looking at the other people's effort, especially other questions on this site, it... |
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