Machine Learning

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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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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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Unsupervised learning explained

Unsupervised learning is used mainly to discover patterns and detect outliers in data today, but could lead to general-purpose AI tomorrow

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Julia vs. Python: Which is best 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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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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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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Natural language processing explained

Deep learning has improved machine translation and other NLP tasks by leaps and bounds

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Deep learning explained

Deep neural networks can solve the most challenging problems, but require abundant computing power and massive amounts of data

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Financial firms bank on A.I. as pilot projects head to production

While AI is a buzzword in financial services, companies must be sure of a business use case even before putting together an AI dev team.

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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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FDA to pilot A.I., consider blockchain, to track and trace food

The FDA plans to pilot artificial intelligence and machine learning technology in its legacy food-screening systems – and it's exploring how to build out blockchain internally and industry-wide to increase the scale, efficiency and...


Delta Lake gives Apache Spark data sets new powers

A new open source project from Databricks adds ACID transactions, versioning, and schema enforcement to Spark data sources that don't have them

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TensorFlow unveils MLIR for faster machine learning

Sublanguage project promises faster compilation and easier hardware optimization for high-performance machine learning models

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IBM preps Watson AI services to run on Kubernetes

IBM Watson services arrive in versions that can run on the public cloud or on privately hosted container infrastructure

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What is Keras? The deep neural network API explained

Easy to use and widely supported, Keras makes deep learning about as simple as deep learning can be

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PyText builds on PyTorch for language recognition

A Facebook project for natural language processing is now open source, and it promises better ways to mine texts for meaning

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Visual Studio Code’s Python add-on tries out data science

Data exploration and machine learning models are enabled via a Python language extension

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