- 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.
Tags: Deep Learning, Dropout, Machine Learning, Mathematics, Textbook
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.
Tags: Deep Learning, Dropout, Python, 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.
Tags: Convolutional Neural Networks, Dropout, Keras
- 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!
Tags: Deep Learning, Dropout, Hyperparameter, Neural Networks, Optimization, Tips
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.
Pages: 1 2
Tags: API, Convolutional Neural Networks, Dropout, Flask, Neural Networks, Python, RESTful API, TensorFlow
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.
Pages: 1 2
Tags: Deep Learning, Dropout, Neural Networks, Representation, Tensor, TensorFlow
- 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.
Pages: 1 2
Tags: Backpropagation, Convolutional Neural Networks, Deep Learning, Dropout, Gradient Descent, LSTM, Neural Networks, Transfer Learning
