Co-founder of consulting firm Neurons Lab and advisor to AI products builders. On Medium, I write about proven strategies for achieving ML technology leadership

Ground principles of reinforcement learning in financial markets

Can you trade a cosine wave before the real markets?

There are many methodologies in algorithmic trading — from automated trade entry and close points based on technical and fundamental indicators to intelligent forecasts and decision making using complex maths and, of course, artificial intelligence. …

Tips for educators and self-trained data scientists

How to learn in the age of commoditized knowledge and commercialized research

Half a year ago I have agreed on a small adventure for myself. My university professor and thesis supervisor Luca di Persio offered me to join a teaching squad at a brand-new Data Science faculty at the University of Verona, my second alma mater. …

To learn new libraries or finally do what the clients want?

Strategies and tactics for independent experts

Remote work is a new normal today. The first months of “freedom” from the office were pretty fun but that job stays the job: dependent on a fixed salary / hourly rate, limited opportunities, risks of losing a warm place. Lots of us have tried to go solo, finding customers…

Don’t make the consultants fool you!

How to satisfy all stakeholders with a great product

Making buzzwords as “digitalization”, “innovation” and “big data” into the alive and profitable product is hard. And usually, it’s not the technology itself that fails, but the alignment between owners, managers, clients, employees, and sometimes the society. …

GANs and other generative machine learning algorithms are still hyped and work fantastically with images, texts, and sounds. They’re able not only to generate data for fun but solve important theoretical issues and boost production ML pipelines. Unfortunately, typical today’s practical use case is limited to “fine-tune pre-trained StyleGAN2 for…

SIMULATIONS, RISKS, AND METRICS

Understanding strategy risk and the probability of overfitting: small numbers that change everything

Note from Towards Data Science’s editors: While we allow independent authors to publish articles in accordance with our rules and guidelines, we do not endorse each author’s contribution. You should not rely on an author’s works without seeking professional advice. See our Reader Terms for details.

This is the third…

SIMULATIONS, RISKS, AND METRICS

Combinatorial and scenario-based backtesting from historical data and simulations

Note from Towards Data Science’s editors: While we allow independent authors to publish articles in accordance with our rules and guidelines, we do not endorse each author’s contribution. You should not rely on an author’s works without seeking professional advice. See our Reader Terms for details.

Let’s disassemble backtests and…

Alexandr Honchar

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store