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How To Train Your Deep Learning Models Faster
Photo by Marc-Olivier Jodoin on Unsplash Deep learning is a subset of machine learning that utilizes neural networks in “deep” architectures, or…
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How to 10x Throughput When Serving Hugging Face Models Without a GPU
By optimising how a model is served, we serve over 100 predictions per second with a simply Python API using…
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Debugging Classifiers with Confusion Matrices
A confusion matrix can provide us with a more representative view of our classifier’s performance, including which specific instances it…
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How to apply machine learning and deep learning methods to audio analysis
To view the code, training visualizations, and more information about the python example at the end of this post, visit…
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Getting Started with Natural Language Processing: US Airline Sentiment Analysis
Sections Introduction to NLP Dataset Exploration NLP Processing Training Hyperparameter Optimization Resources for Future Learning Introduction to NLP Natural Language…
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Codeless Deep Learning Pipelines with Ludwig and comet.ml
How to use Ludwig and comet.ml together to build powerful deep learning models right in your command line — using…
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Approach pre-trained deep learning models with caution
Pre-trained models are easy to use, but are you glossing over details that could impact your model performance? How…
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A CNN can learn Miró’ surrealism: Joan Miró Neural Style Transfer & DeepDream
Note: this article originally appeared on Raúl Gómez’s website at https://gombru.github.io/2019/01/14/miro_styletransfer_deepdream/ and was reposted here with his permission. We highly encourage…
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Real-time numbers recognition (MNIST) on an iPhone with CoreML from A to Z
Learn how to build and train a deep learning network to recognize numbers (MNIST), how to convert it in the…
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Building reliable machine learning models with cross-validation
Cross-validation is a technique used to measure and evaluate machine learning models performance. During training we create a number of…