Viewing profile — prostodata

> pull everything to my PC and use pandas, to take advantage of its ability to build up results piece by piece. Most difficulties in data processing arise from the need to process …

It should be noted that the expression like comp = salary / (age - 18) is (strictly speaking) not part of the relational algebra because it is not using set operations (like join o…

Here are some major issues [1]: SQL’s shortcomings can be grouped into these categories: - lack of proper orthogonality — SQL is hard to compose; - lack of compactness — SQL is a l…

Just for comparison, a functional approach is a major alternative to relational and set-oriented models and query languages. The difference is that functions and operations with fu…

Here is one possible implementation of the concept-oriented model of data for data processing. It heavily relies on functions and operations with functions and is an alternative to…

For example, I have data from 1900 till 2000. I train ARMA using this data by storing the corresponding coefficients as model parameters. Now I get data from 2010 to 2020. My goal …

In fact, there are two general approaches to unifying ML with time series: o Unifying ML API and patterns so that time series can be analyzed in the same way as normal tabular data…

When I see a new forecasting library, my first question is whether it can apply ARIMA in a sklearn manner by training a model using (large) train time series X, storing the model b…

Anomaly detection belongs to unsupervised learning while in time series analysis we normally think about future and future values are viewed as labels. One approach to think in ter…

> No, the relational model is beautiful and consistent! SQL is messy... What is beautiful and consistent is the relational algebra. The relation model relies on this formalism to m…

I think both conceptions are important. On one hand, some code is naturally related to certain data and hence we should accordingly design the program. On the other hand, complex a…

> I am currently working on complex (JOIN and aggregates) queries without any SQL knowledge One way to process data without joins and groupy in multiple tables is to use Prosto too…

Apache Pulsar should not be confused with another quite popular Pulsar: Event driven concurrent framework for Python https://github.com/quantmind/pulsar

In the context of computer science, matrices are used as a representation construct with different possible formal interpretations which frequently can be recognized depending on t…

Here is another project for working with CAN: https://github.com/hardbyte/python-can I used it (as well as Cantools) for importing various CAN-specific data formats.

Does it relate somehow to Intel SGX (Software Guard Extensions): https://en.wikipedia.org/wiki/Software_Guard_Extensions

PyTorch is simpler, easer to use, consumes less memory and allows for dynamic dynamic computational graphs (dynamic operations during the forward pass).

Is there any (significant) difference between sharding and load balancing? It seems that in both cases the idea is to distribute (supposedly independent) requests between workers a…

Several classical methods for time series forecasting including ARIMA are described here: https://machinelearningmastery.com/time-series-forecasting-m...