Data Science

Data Science news, information, and how-to advice

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What’s new in Python 3.7

Python 3.7 adds new classes for data handling, optimizations for script compilation and garbage collection, and faster asynchronous I/O

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Handing off models from data science to IT

The relationship between your data science and IT teams can complicate the deployment of analytic models

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TensorFlow review: The best deep learning library gets better

At version r1.5, Google's open source machine learning and neural network library is more capable, more mature, and easier to learn and use


Data democratization: finally living up to the name

Defining data democratized.

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Get started with Anaconda Python, the distro for data science

It provides a management GUI, a slew of scientifically oriented work environments, and tools to simplify the process of using Python for data crunching

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Fighting the gender gap in data science

As data science begins to infiltrate more and more industries, proving to be crucial for market competitiveness, women are slowly starting to see change. Here are some women, programs, and organizations leading the way

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Julia vs. Python: Julia language rises for data science

Python has turned into a data science and machine learning mainstay, while Julia was built from the ground up to do the job

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8 tips to ask smarter questions of your data scientists

Some guidelines for the intimidated business leader to get the most of their data science team

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Where are you in your analytical journey?

5 stages of the analytic process for data scientists and IT, plus a few best practices for tackling those stages.

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4 careers where data science skills will help you get ahead

As the talent gap widens companies will likely require or at least encourage a certain level of data savvy from nontechnical team members to stay competitive in the market

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Modern IT and data science in an era of analytic deployment

How data scientists and IT build and deploy their analytics models

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What’s new in TensorFlow machine learning

Google's TensorFlow 1.4 machine learning library adds the contributed Dataset API for working with data sources, but watch out for breakage caused by the update

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Can data scientists tackle the IoT demand?

Current and future data scientists should consider the impact IoT will have in the field, especially because companies investing in IoT will need data experts

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Review: automates machine learning

Driverless AI really is able to create and train good machine learning models without requiring machine learning expertise from users

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What’s new in the Anaconda distribution for Python

Version 5.0.1 of the math-, science-, and data-analysis-focused distribution for Python uses newly recompiled binaries


Even data scientists are facing AI takeover

As euphemisms fly for AI replacing human activity, data scientists start to experience the benefits and risks of AI-assisted automation

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5 essential Python tools for data science—now improved

SciPy, Cython, Dask, HPAT, and Numba all have new versions that aid big data analytics and machine learning projects

Why cloud platforms should invest in the promise of Python

Python has emerged as the language developers want to use more than any other for building data-intensive projects. Python now powers some of the most complex applications on the cloud

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