Nothing but NumPy: Understanding & Creating Neural Networks with Computational Graphs from Scratch - Aug 23, 2019.
Entirely implemented with NumPy, this extensive tutorial provides a detailed review of neural networks followed by guided code for creating one from scratch with computational graphs.
Backpropagation, Neural Networks, numpy, Python
- KDnuggets™ News 19:n21, Jun 5: Transitioning your Career to Data Science; 11 top Data Science, Machine Learning platforms; 7 Steps to Mastering Intermediate ML w. Python - Jun 5, 2019.
The results of KDnuggets 20th Annual Software Poll; How to transition to a Data Science career; Mastering Intermediate Machine Learning with Python ; Understanding Natural Language Processing (NLP); Backprop as applied to LSTM, and much more.
Backpropagation, Data Science Platform, LSTM, Machine Learning, NLP, Python
- Understanding Backpropagation as Applied to LSTM - May 30, 2019.
Backpropagation is one of those topics that seem to confuse many once you move past feed-forward neural networks and progress to convolutional and recurrent neural networks. This article gives you and overall process to understanding back propagation by giving you the underlying principles of backpropagation.
Backpropagation, LSTM, Neural Networks, Recurrent Neural Networks
- The Backpropagation Algorithm Demystified - Jan 2, 2019.
A crucial aspect of machine learning is its ability to recognize error margins and to interpret data more precisely as rising numbers of datasets are fed through its neural network. Commonly referred to as backpropagation, it is a process that isn’t as complex as you might think.
Backpropagation, Explained, Neural Networks
- Deep Learning in H2O using R - Jan 22, 2018.
This article is about implementing Deep Learning (DL) using the H2O package in R. We start with a background on DL, followed by some features of H2O's DL framework, followed by an implementation using R.
Backpropagation, Deep Learning, Gradient Descent, H2O, Machine Learning, R
- Top KDnuggets tweets, Dec 06-12: Top #DataScience and #MachineLearning Methods Used in 2017; Geoff Hinton Capsule Networks – a new way for machines to see - Dec 13, 2017.
Also The first international #beauty contest decided by #AI #algorithm sparked controversy; 4 Common #Data Fallacies That You Need To Know; Using #DeepLearning to Solve Real World Problems; Best Online Masters in #DataScience and #Analytics.
AI, Backpropagation, Bias, Capsule Networks, Data Science Tools, Geoff Hinton, Regression, Top tweets
- 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
Backpropagation, Convolutional Neural Networks, Deep Learning, Dropout, Gradient Descent, LSTM, Neural Networks, Transfer Learning
- Neural Network Foundations, Explained: Updating Weights with Gradient Descent & Backpropagation - Oct 25, 2017.
In neural networks, connection weights are adjusted in order to help reconcile the differences between the actual and predicted outcomes for subsequent forward passes. But how, exactly, do these weights get adjusted?
Backpropagation, Explained, Gradient Descent, Neural Networks
- A Quick Introduction to Neural Networks - Nov 9, 2016.
This article provides a beginner level introduction to multilayer perceptron and backpropagation.
Pages: 1 2 3
Backpropagation, Deep Learning, Machine Learning, Neural Networks
- Top KDnuggets tweets, Jun 15-21: Predicting UEFA Euro2016; Visual Explanation of Backprop for Neural Nets - Jun 22, 2016.
Building statistical model to predict UEFA #Euro2016; A Visual Explanation of Back Propagation Algorithm for #NeuralNetworks; Scala is the new golden child for coding and #DataScience.
Backpropagation, Football, Scala, Soccer, Top tweets, Yahoo
- KDnuggets™ News 16:n22, Jun 22: Data Science Blog Contest; Free Machine Learning Ebook; Master SQL for Data Science - Jun 22, 2016.
Data Science Blog Contest; New Free Andrew Ng Machine Learning Book Under Construction; 7 Steps to Mastering SQL for Data Science; A Visual Explanation of the Back Propagation Algorithm; Mining Twitter Data with Python Part 1: Collecting Data
Backpropagation, Data Science, Free ebook, Neural Networks, SQL
- A Visual Explanation of the Back Propagation Algorithm for Neural Networks - Jun 17, 2016.
A concise explanation of backpropagation for neural networks is presented in elementary terms, along with explanatory visualization.
Algorithms, Backpropagation, Explanation, Machine Learning, Neural Networks
- Learning to Code Neural Networks - Jan 22, 2016.
Learn how to code a neural network, by taking advantage of someone else's experiences learning how to code a neural network.
Pages: 1 2
Backpropagation, Denny Britz, Neural Networks, Python
- How do Neural Networks Learn? - Dec 2, 2015.
Neural networks are generating a lot of excitement, while simultaneously posing challenges to people trying to understand how they work. Visualize how neural nets work from the experience of implementing a real world project.
Backpropagation, Graph Visualization, Neural Networks
- A Neural Network in 11 lines of Python - Oct 30, 2015.
A bare bones neural network implementation to describe the inner workings of back-propagation.
Pages: 1 2 3
Backpropagation, IPython, Neural Networks, Prediction, Python
- YCML Machine Learning library on Github - Aug 24, 2015.
YCML is a new Machine Learning library available on Github as an Open Source (GPLv3) project. It can be used in iOS and OS X applications, and includes Machine Learning and optimization algorithms.
Backpropagation, GitHub, iOS, Machine Learning, Open Source, Optimization
- Geoff Hinton AMA: Neural Networks, the Brain, and Machine Learning - Dec 9, 2014.
In a wide-ranging Q&A, Geoff Hinton addresses the future of deep learning, its biological inspirations, and his research philosophy.
Backpropagation, Deep Learning, Geoff Hinton, Michael Jordan, Neural Networks, Neuroscience, Zachary Lipton
