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Kateryna Lytvynova

How to Organize Data Labeling for Machine Learning: Approaches and Tools

August 15, 2019 by Kateryna Lytvynova

data annotation

If there was a data science hall of fame, it would have a section dedicated to labeling. The labelers’ monument could be Atlas holding that large rock symbolizing their arduous, detail-laden responsibilities. ImageNet — an image database — would deserve its own style. For nine years, its contributors manually annotated more than 14 million images. Just thinking about it makes … [Read more...] about How to Organize Data Labeling for Machine Learning: Approaches and Tools

Machine Learning Project Structure: Stages, Roles, and Tools

July 23, 2019 by Kateryna Lytvynova

Machine Learning Project

Various businesses use machine learning to manage and improve operations. While ML projects vary in scale and complexity requiring different data science teams, their general structure is the same. For example, a small data science team would have to collect, preprocess, and transform data, as well as train, validate, and (possibly) deploy a model to do a single … [Read more...] about Machine Learning Project Structure: Stages, Roles, and Tools

Sentiment Analysis: Types, Tools, and Use Cases

May 14, 2019 by Kateryna Lytvynova

sentiment analysis

What do you do before purchasing something that costs more than a pack of gum? Whether you want to treat yourself to new sneakers, a laptop, or an overseas tour, processing an order without checking out similar products or offers and reading reviews doesn’t make much sense any more. Thanks to comment sections on eCommerce sites, social nets, review platforms, or dedicated … [Read more...] about Sentiment Analysis: Types, Tools, and Use Cases

Reinforcement Learning Explained: Overview, Comparisons and Applications in Business

May 14, 2019 by Kateryna Lytvynova

reinforcement learning

Imagine you’re completing a mission in a computer game. Maybe you’re going through a military depot to find a secret weapon. You get points for the right actions (killing an enemy) and lose them for the wrong ones (falling into a pit or getting hit). If you’re playing on high difficulty, you might not conclude this task in just one attempt. Try after try, you learn which … [Read more...] about Reinforcement Learning Explained: Overview, Comparisons and Applications in Business

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