- Generalization in Neural Networks - Nov 18, 2019.
When training a neural network in deep learning, its performance on processing new data is key. Improving the model's ability to generalize relies on preventing overfitting using these important methods.
- Designing Your Neural Networks - Nov 4, 2019.
Check out this step-by-step walk through of some of the more confusing aspects of neural nets to guide you to making smart decisions about your neural network architecture.
- KDnuggets™ News 18:n34, Sep 12: Essential Math for Data Science; 100 Days of Machine Learning Code; Drop Dropout - Sep 12, 2018.
Also: Neural Networks and Deep Learning: A Textbook; Don't Use Dropout in Convolutional Networks; Ultimate Guide to Getting Started with TensorFlow.
- Ultimate Guide to Getting Started with TensorFlow - Sep 6, 2018.
Including video and written tutorials, beginner code examples, useful tricks, helpful communities, books, jobs and more - this is the ultimate guide to getting started with TensorFlow.
- Don’t Use Dropout in Convolutional Networks - Sep 5, 2018.
If you are wondering how to implement dropout, here is your answer - including an explanation on when to use dropout, an implementation example with Keras, batch normalization, and more.
- Deep Learning Tips and Tricks - Jul 4, 2018.
This post is a distilled collection of conversations, messages, and debates on how to optimize deep models. If you have tricks you’ve found impactful, please share them in the comments below!
- Complete Guide to Build ConvNet HTTP-Based Application using TensorFlow and Flask RESTful Python API - May 15, 2018.
In this tutorial, a CNN is to be built, and trained and tested against the CIFAR10 dataset. To make the model remotely accessible, a Flask Web application is created using Python to receive an uploaded image and return its classification label using HTTP.
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- A “Weird” Introduction to Deep Learning - Mar 30, 2018.
There are amazing introductions, courses and blog posts on Deep Learning. But this is a different kind of introduction.
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- The 10 Deep Learning Methods AI Practitioners Need to Apply - Dec 13, 2017.
Deep learning emerged from that decade’s explosive computational growth as a serious contender in the field, winning many important machine learning competitions. The interest has not cooled as of 2017; today, we see deep learning mentioned in every corner of machine learning.
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