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Launched in 2010, Lyst is a revolutionary way to shop for fashion online that’s used by millions every month. We partner with the world’s top fashion brands and stores to provide people with a personalised way to discover the fashion they love. We believe in crafting a new way to shop - one that's centred around the user. Our database of more than 5 million products is being built and updated by hundreds of spiders crawling hundreds of sites and the web for data and - since web is constantly changing - we need to remain at the top of our game.
This data is just the raw material starting its way on ‘conveyor belt’ of further processing. Each step needs to be done with care and we need to be proficient in understanding which products changed and how, so we can notify our users when their favorite item is back in stock or has been discounted. Nothing disappoints more than a false promise of a good deal.
To handle this we invest a lot in machine learning - think SVMs, Random Forest, PCA, SVD, SGD, k-mean, KNN, function optimization. We need them to scale - so we create small event-based services that communicate with each other.
Because we store too many products for anyone to list through, we need to help our customers find products they like. Our recommendation system, based on “Weighted Alternating Least Squares” and “Collaborative Filtering for Implicit Feedback Datasets”, includes ranking and merchandising and we work hard to make it even better. Fashion is very personal so recommendations should be too.
Lyst is growing quickly - we grew 400% in 2013, with a annual run rate of $60million in sales for the the leading fashion partners we work with. We are very proud to be backed by a range of all-star investors including Balderton (Yoox, MySQL), Accel Partners (Facebook, Spotify), DFJ (Skype, Hotmail) and the teams behind Oscar de la Renta and Tory Burch.
http://www.python-academy.com/
Python Academy is a specialized Python training company. We offer open courses for individuals as well as customized on-site courses for companies and institutes. We cover a wide range of Python topics from introductory to advanced, Python for scientists and engineers, web development, code optimization and many more.
In addition to training, we consult companies that migrate to Python and develop high-quality Python software often in combination with training. Our special expertise is scientific and technical software development with Python.
Launched in 2010, Lyst is a revolutionary way to shop for fashion online that’s used by millions every month. We partner with the world’s top fashion brands and stores to provide people with a personalised way to discover the fashion they love. We believe in crafting a new way to shop - one that's centred around the user. Our database of more than 5 million products is being built and updated by hundreds of spiders crawling hundreds of sites and the web for data and - since web is constantly changing - we need to remain at the top of our game.
This data is just the raw material starting its way on ‘conveyor belt’ of further processing. Each step needs to be done with care and we need to be proficient in understanding which products changed and how, so we can notify our users when their favorite item is back in stock or has been discounted. Nothing disappoints more than a false promise of a good deal.
To handle this we invest a lot in machine learning - think SVMs, Random Forest, PCA, SVD, SGD, k-mean, KNN, function optimization. We need them to scale - so we create small event-based services that communicate with each other.
Because we store too many products for anyone to list through, we need to help our customers find products they like. Our recommendation system, based on “Weighted Alternating Least Squares” and “Collaborative Filtering for Implicit Feedback Datasets”, includes ranking and merchandising and we work hard to make it even better. Fashion is very personal so recommendations should be too.
Lyst is growing quickly - we grew 400% in 2013, with a annual run rate of $60million in sales for the the leading fashion partners we work with. We are very proud to be backed by a range of all-star investors including Balderton (Yoox, MySQL), Accel Partners (Facebook, Spotify), DFJ (Skype, Hotmail) and the teams behind Oscar de la Renta and Tory Burch.
Based in London, Knowsis is a web intelligence company building next generation financial markets data. We use Machine Learning, Natural Language Processing and statistical analysis to extract value from non-traditional online sources into quantifiable and actionable output for the financial sector.
Our mission is to develop and market products/services that bridge the information gap between the global financial sector and the social web.
