Dataconomy

JULY 31, 2017

Introduction A couple of months ago a client of mine asked me the following question: “What is the faster data structure object in Python for Big Data analysis today?” I get questions like this one all the time. Some of them are not easy to solve at all and it. The post High Performance Big Data Analysis Using NumPy, Numba & Python Asynchronous Programming appeared first on Dataconomy.

Data Analysis 183

Data Analysis Data Analysis Big Data Big Data 183

Ines Montani

AUGUST 4, 2017

I’m excited and proud to finally share what we’ve been working on since launching Explosion AI , alongside our NLP library spaCy and our consulting projects. Prodigy is a project very dear to my heart and seeing it come to life has been one of the most exciting experiences as a software developer so far. A lot of the consulting projects we’ve worked on in the past year ended up circling back to the problem of labelling data to train custom models.

Python 52

Python Supervised Learning Artificial Intelligence Artificial Intelligence 52

Explosion

AUGUST 3, 2017

Machine learning systems are built from both code and data. It’s easy to reuse the code but hard to reuse the data, so building AI mostly means doing annotation. This is good, because the examples are how you program the behaviour – the learner itself is really just a compiler. What’s not good is the current technology for creating the examples. That’s why we’re pleased to introduce Prodigy , a downloadable tool for radically efficient machine teaching.

Supervised Learning 52

Supervised Learning Python Machine Learning Machine Learning 52

Depends on the Definition

JULY 29, 2017

In this post we will introduce multivariate adaptive regression splines model (MARS) using python. This is a regression model that can be seen as a non-parametric extension of the standard linear model.

Python 52

Python 52

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AI

Dataconomy

AUGUST 4, 2017

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Big Data 178

Big Data Big Data Data Science Analytics 178

Christian Haschek

AUGUST 3, 2017

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Depends on the Definition

JULY 31, 2017

When running experiments with deep neural nets you want to use appropriate hardware. Most of the time I work on a thinkpad laptop with no GPU. This makes experimenting painfully slow. A convenient way is to use an AWS instance, for example the p2.

AWS 40

AWS Deep Learning Deep Learning 40

Dataconomy

AUGUST 2, 2017

One of the great things about running a startup is that you’re working with a clean slate. If you have worked with a different organization before, you may have had issues with culture and people that you probably don’t want happening with your own company. Existing organizations, especially the established. The post How to promote a culture of data stewardship for your startup appeared first on Dataconomy.

Data Science 164

Data Science 164

Explosion

AUGUST 3, 2017

Machine learning systems are built from both code and data. It's easy to reuse the code but hard to reuse the data, so building AI mostly means doing annotation. This is good, because the examples are how you program the behaviour – the learner itself is really just a compiler. What's not good is the current technology for creating the examples. That's why we're pleased to introduce Prodigy, a downloadable tool for radically efficient machine teaching.

Machine Learning 40

Machine Learning Machine Learning AI AI 40