Posts

Machine Learning in Science and Industry slides

Hamiltonian Monte Carlo explained

Jupyter (IPython) notebooks features

Occam razor vs. machine learning

MLHEP 2016 lectures slides

Gradient Boosting Interactive Playground

Gradient Boosting explained [demonstration]

.new_item for python lists

Interactive demonstrations for ML courses

Testing implementations of LibFM

Reconstructing pictures with machine learning [demonstration]

Optimal control of oscillations [demonstration]

Cumulative sum as a test for your programming environment

Rule of statistical error

Using fortran from python

So you decided to write a machine learning library (bad advice)

Reweighting with Boosted Decision Trees

sPlot: a technique to reconstruct components of mixture

ROC curve demonstration

Data manipulation with numpy: tips and tricks, part 2

Data manipulation with numpy: tips and tricks, part 1

Loglikelihood benchmark

MLHEP 2015 lectures slides

Machine learning in COMET experiment (part II)

Multimixture fitting

LibFM in python

Do you know that convolution operation is implemented in deep learning systems via matrix multiplication?

Learning to rank (software, datasets)

A Programming Language

Practical tasks on bioinformatics

Machine learning used in tracking of COMET (japanese particle physics experiment), part I

Automatic reweighting with gradient boosting

Decision train classifier

Removing margins of PDFs

Back to the future (vector representation of future, an approach to analysis of time series)

Theanobased libraries for machine learning

Tensor train

Very deep neural network

Anomaly detection at CERN experiments

Numpy tricks (again)

Links on deep learning

Vector representations of categories

Code and the importance of vectorization

Numpy exercises

Plans for ML experiments

Simplification vs usability

Good list of NN training methods

Pairwise layer in neural network

Interactive introduction to structure of CPU

An interesting equality from linear algebra

Benchmarks of speed (Numpy vs all)

Why using HDF5?

Neural Networks

So many names

Cousteau

Optimization of vector operations

Minibus stochastic process (part 1)

Theano (python library)

No Free Lunch

Divergent series

Numbers and Naturalness, part 3

Legendre transformation without Legendre transformation

Redundant numeral systems

Soviet computer "Сетунь"

Numbers and Naturalness, part 2.

Numbers and Naturalness, part 1.

Why and What
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