Domino Data Science Blog
![Nikolay Manchev](https://cdn.sanity.io/images/kuana2sp/production-main/5338350cde5bdf48017d146846ea64a2685e86f1-800x800.png?w=600&fit=max&auto=format)
Nikolay Manchev
Nikolay Manchev is a former Principal Data Scientist for EMEA at Domino Data Lab. In this role, Nikolay helped clients from a wide range of industries tackle challenging machine learning use-cases and successfully integrate predictive analytics in their domain-specific workflows. He holds an MSc in Software Technologies, an MSc in Data Science, and is currently undertaking postgraduate research at King's College London. His area of expertise is Machine Learning and Data Science, and his research interests are in neural networks and computational neurobiology.
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Reinforcement learning: The K-armed bandit problem
In a previous blog post we talked about the foundations of reinforcement learning. We covered classical and operant conditioning, rewards, states, and actions, and did a review of some common reinforcement learning use-cases. This entry is a continuation of the series. In it, we present the k-armed bandit problem - a very simple setting that enables us to introduce the interaction between some of the key components of reinforcement learning.
By Nikolay Manchev9 min read
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Spark, Dask, and Ray: choosing the right framework
Apache Spark, Dask, and Ray are three of the most popular frameworks for distributed computing. In this blog post we look at their history, intended use-cases, strengths and weaknesses, in an attempt to understand how to select the most appropriate one for specific data science use-cases.
By Nikolay Manchev15 min read
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Building a named entity recognition model using a BiLSTM-CRF network
By Nikolay Manchev13 min read
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Fitting support vector machines via quadratic programming
In this blog post we take a deep dive into the internals of Support Vector Machines. We derive a Linear SVM classifier, explain its advantages, and show what the fitting process looks like when solved via CVXOPT — a convex optimization package for Python.
By Nikolay Manchev18 min read
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GPU-accelerated Convolutional Neural Networks with PyTorch
Convolutional Neural Networks (CNNs and also ConvNets) is a class of Neural Networks typically used for image classification (mapping image data to class values). At a high level, CNNs can be viewed simply as a variant of feedforward networks, but they have a number of advantages in comparison to more traditional algorithms for analysing visual imagery.
By Nikolay Manchev13 min read
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Eight Considerations When Choosing a Data Store for Data Science
Selecting the right technology that enables data scientists to focus on data science and not IT infrastructure will help enterprises reap the benefits of their investments in data science and machine learning.
By Nikolay Manchev18 min read
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