Data Science

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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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What is TensorFlow? The machine learning library explained

TensorFlow is a Python-friendly open source library for numerical computation that makes machine learning faster and easier

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What’s new in TensorFlow 2.0

Google’s TensorFlow 2.0 is now available in beta, with a focus on improving performance, ease, compatibility, and continuity

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The best new features in Python 3.8

From a powerful new assignment syntax to under-the-hood overhauls, Python 3.8 steps toward a more modern Python codebase

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Reinforcement learning explained

Reinforcement learning uses rewards and penalties to teach computers how to play games and robots how to perform tasks independently

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Machine learning explained

Able to learn from data, machine learning algorithms can solve problems that are too complex to solve with conventional programming

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Machine learning algorithms explained

Machine learning uses algorithms to turn a data set into a model. Which algorithm works best depends on the problem

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What is Jupyter Notebook? Data analysis made easier

Jupyter Notebook combines live code, graphics, visualizations, and text in shareable notebooks that run in a web browser


Mozilla brings Python data science to the browser

Pyodide project uses Emscripten and WebAssembly to run Python and its data science libraries in any major browser

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Review: Google Cloud AutoML is truly automated machine learning

Google’s AutoML lets you create customized deep learning models without any knowledge of data science or programming

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5 reasons data science belongs in the cloud

Why laptop-hugging data scientists and server-hugging machine learning practitioners should consider letting go

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Python tutorial: Get started with Jupyter Notebook

Learn how to combine Python code, freeform text, mathematical formulas, and graphics in an interactive, shareable notebook

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Guided automation for machine learning

Implementing a web-based blueprint for semi-automated machine learning, using the open source Knime Analytics Platform

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How to automate machine learning

KNIME’s blueprint for guided automation allows business analysts to train, test, and tune machine learning models via web browser

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Review: MXNet deep learning shines with Gluon

With the addition of the high-level Gluon API, Apache MXNet rivals TensorFlow and PyTorch for developing deep learning models

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How to use Knime for data science

Free, open-source Knime allows you to visually assemble data processing “nodes” into machine learning, deep learning, and other analytics workflows

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Microsoft revamps machine learning tools for Apache Spark

The new open source release integrates Spark with Cognitive Toolkit and other Microsoft machine learning offerings

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