Data Science

Data Science | News, how-tos, features, reviews, and videos

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Pandas 1.0 brings big breaking changes

The first major point release of the powerful Python data analysis package removes many features and deprecates many others

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Netflix open sources data science management tool

Metaflow manages Python data science projects end-to-end, works with any machine learning library, and integrates with AWS cloud services

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Simplifying data management in the cloud

Enterprises are bogged down in a sea of data complexity as they expand the use of cloud-native databases. Could self-identifying data be the answer?

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6 best programming languages for AI development

Which programming language should you pick for your machine learning or deep learning project? These are your best options

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Handicapping the AI modeling horse race

AI has become a core focus for application developers everywhere. It’s as hot in the consumer space as it is in business, industry, research, and government

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Data science and cloud computing win most political campaigns

With the 2020 elections a year away, technology will play a bigger role than policy. Enterprises should learn something

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Why retailers can’t get enough data scientists

As the retail apocalypse continues – with an estimated 8,600 closing their doors in 2019 – other retail survivors are upping their game with hard-to-find data scientists

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Google previews site for sharing machine learning experiments

TensorBoard.dev allows you to upload and share TensorBoards and visualize model graphs and metrics

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Data integration platforms every developer should understand

Knowing the new data practices and machine learning technologies is vital for software developers to create business value

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Artificial intelligence today: What’s hype and what’s real?

Two decades into the AI revolution, deep learning is becoming a standard part of the analytics toolkit. Here’s what it means

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Semi-supervised learning explained

Using a machine learning model’s own predictions on unlabeled data to add to the labeled data set sometimes improves accuracy, but not always

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PyTorch vs. TensorFlow: How to choose

If you actually need a deep learning model, PyTorch and TensorFlow are the two leading options

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Deep learning frameworks: PyTorch vs. TensorFlow

If you actually need a deep learning model, PyTorch and TensorFlow are both good choices

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Automated machine learning or AutoML explained

AutoML frameworks and services eliminate the need for skilled data scientists to build machine learning and deep learning models

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Stop searching for that data scientist unicorn

Instead, focus on hiring the technical skills needed to build the team, and the soft skills needed to work on the team

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Applying devops in data science and machine learning

Having data scientists collaborate with devops and engineers leads to better business outcomes, but understanding their different requirements is key

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The best machine learning and deep learning libraries

TensorFlow, Spark MLlib, Scikit-learn, PyTorch, MXNet, and Keras shine for building and training machine learning and deep learning models

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The best machine learning and deep learning libraries

TensorFlow, Spark MLlib, Scikit-learn, PyTorch, MXNet, and Keras shine for building and training machine learning and deep learning models

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TensorFlow 2 review: Easier machine learning

Now more platform than toolkit, TensorFlow has made strides in everything from ease of use to distributed training and deployment

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Supervised learning explained

Supervised learning turns labeled training data into a tuned predictive model

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