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 7 Steps to Mastering Deep Learning with Keras
By Matthew Mayo, KDnuggets Managing Editor on October 30, 2017 in 7 Steps, Convolutional Neural Networks, Deep Learning, Keras, Logistic Regression, LSTM, Machine Learning, Neural Networks, Python, Recurrent Neural NetworksAre you interested in learning how to use Keras? Do you already have an understanding of how neural networks work? Check out this lean, fat-free 7 step plan for going from Keras newbie to master of its basics as quickly as is possible.
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Neural Networks, Step 1: Where to Begin with Neural Nets & Deep Learning
This is a short post for beginners learning neural networks, covering several essential neural networks concepts.
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Neural Network Foundations, Explained: Updating Weights with Gradient Descent & Backpropagation
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?
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5 Free Resources for Furthering Your Understanding of Deep Learning
This post includes 5 specific video-based options for furthering your understanding of neural networks and deep learning, collectively consisting of many, many hours of insights.
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Python Data Preparation Case Files: Group-based Imputation
The second part in this series addresses group-based imputation for dealing with missing data values. Check out why finding group means can be a more formidable action than overall means, and see how to accomplish it in Python.
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 30 Essential Data Science, Machine Learning & Deep Learning Cheat Sheets
By Matthew Mayo, KDnuggets Managing Editor on September 22, 2017 in Cheat Sheet, Data Science, Deep Learning, Machine Learning, Neural Networks, Probability, Python, R, SQL, StatisticsThis collection of data science cheat sheets is not a cheat sheet dump, but a curated list of reference materials spanning a number of disciplines and tools.
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Keras Tutorial: Recognizing Tic-Tac-Toe Winners with Neural Networks
In this tutorial, we will build a neural network with Keras to determine whether or not tic-tac-toe games have been won by player X for given endgame board configurations. Introductory neural network concerns are covered.
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Python Data Preparation Case Files: Removing Instances & Basic Imputation
This is the first of 3 posts to cover imputing missing values in Python using Pandas. The slowest-moving of the series (out of necessity), this first installment lays out the task and data at the risk of boring you. The next 2 posts cover group- and regression-based imputation.
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Neural Network Foundations, Explained: Activation Function
This is a very basic overview of activation functions in neural networks, intended to provide a very high level overview which can be read in a couple of minutes. This won't make you an expert, but it will give you a starting point toward actual understanding.
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277 Data Science Key Terms, Explained
This is a collection of 277 data science key terms, explained with a no-nonsense, concise approach. Read on to find terminology related to Big Data, machine learning, natural language processing, descriptive statistics, and much more.
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7 Steps to Mastering Deep Learning with Keras
30 Essential Data Science, Machine Learning & Deep Learning Cheat Sheets
277 Data Science Key Terms, Explained