They will also tell you that the true cost includes not merely the dollars you spend, but there is a…

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## RNNs: The Trade-Off Between Long-Term Memory and Smoothness

RNNs: The Trade-Off Between Long-Term Memory and SmoothnessZachary ManesiotisBlockedUnblockFollowFollowingJun 20It is well-known that retaining long-term information when learning via gradient…

Continue Reading## Design Patterns: The Decorator Pattern

Design Patterns: The Decorator PatternLearn how to make your code cleaner and more modular with the Decorator patternNitin VermaBlockedUnblockFollowFollowingMay 6Prerequisites:If…

Continue Reading## Hyperparameter Tuning with callbacks in Keras

Hyperparameter Tuning with callbacks in KerasAbhishek RajbhojBlockedUnblockFollowFollowingMay 5Why is this important ?Applied Machine Learning is an empirical process where you need to…

Continue Reading## An overview of the Gradient Descent algorithm

That explains why the least squared loss works for a wide range of problems. The underlying noise is very often…

Continue Reading## Fraud detection with cost-sensitive machine learning

Let’s assume the following scenario. If a fraudulent transaction is not recognized by the system, the money is lost and…

Continue Reading## Understanding the Mathematics behind Gradient Descent.

Because the squared differences make it easier to derive a regression line. Indeed, to find that line we need to…

Continue Reading## Introduction to FeedForward Neural Networks

Introduction to FeedForward Neural NetworksYash upadhyayBlockedUnblockFollowFollowingMar 7SourceDeep Feedforward networks or also known multilayer perceptrons are the foundation of most deep learning…

Continue Reading## Generative Adversarial Networks: Revitalizing old video game textures

Generative Adversarial Networks: Revitalizing old video game texturesEdward BarnettBlockedUnblockFollowFollowingFeb 28A pixel art gif I generated with the model. Not too shabby. If…

Continue Reading## How to do Cost-Sensitive Learning

How to do Cost-Sensitive LearningBe right in classification modeling when it matters mostJoe Tenini, PhDBlockedUnblockFollowFollowingFeb 25IntroductionData Science teams must often walk…

Continue Reading## Exploring Cost Optimisation on AWS

Exploring Cost Optimisation on AWSAayush KumarBlockedUnblockFollowFollowingFeb 25In the present day scenario, people really value that moment of instant gratification they get…

Continue Reading## Understanding Logistic Regression step by step

Understanding Logistic Regression step by stepTraining a logistic regression classifier to predict people’s gender based on their weight and height. Gustavo ChávezBlockedUnblockFollowFollowingFeb…

Continue Reading## Build your own Neural Network-2: Our first neural network architecture

In order to do so, we need a labeled data from which the neural network can learn from. We call…

Continue Reading## Machine Leaning: Cost Function and Gradient Descend

Let’ see…Cost FunctionCost function basically means how much far away your predicted line is from the actual points that we…

Continue Reading## Introduction to Classification for Beginners

Introduction to Classification for BeginnersAditya ChandupatlaBlockedUnblockFollowFollowingJan 20Supervised Machine Learning can be broadly classified into two categories:RegressionClassificationWhile regression allows you to…

Continue Reading## The REAL Correct Way to Handle Missing Data

Simple. You talk to your client. Now, this answer is so short, and so simple, that for some of you…

Continue Reading## Everything you need to know about Neural Networks and Backpropagation — Machine Learning Made Easy and Fun

Everything you need to know about Neural Networks and Backpropagation — Machine Learning Made Easy and FunNeural Network explanation from the ground including…

Continue Reading## Andrew Ng’s Machine Learning Course in Python (Anomaly Detection)

Andrew Ng’s Machine Learning Course in Python (Anomaly Detection)Benjamin LauBlockedUnblockFollowFollowingJan 12Machine Learning — Andrew NgThis is the last part of Andrew Ng’s Machine…

Continue Reading## Hitting the ground with Linear Regression

Hitting the ground with Linear RegressionAditya ChandupatlaBlockedUnblockFollowFollowingJan 12Statistically speaking, regression is a technique used to determine the statistical relationship between…

Continue Reading## Dynamic Programming: Cutting Sticks

Dynamic Programming: Cutting SticksTiagoBlockedUnblockFollowFollowingJan 7This article will walk you through a problem called Cutting Sticks¹ from UVA (Universidad de Valladolid)’s problem…

Continue Reading## For the love of regression

For the love of regressionSyed MisbahBlockedUnblockFollowFollowingJan 3Regression is used to model the relationship between a dependent variable and one or…

Continue Reading## Uncertainty in machine learning predictions

Your cost function in this case will not penalize when either 1 or 7 is predicted, but will penalize when…

Continue Reading## Andrew Ng’s Machine Learning Course in Python (Neural Networks)

The optimizing algorithm I am using is once again the same old gradient descent.def gradientDescentnn(X,y,initial_nn_params,alpha,num_iters,Lambda,input_layer_size, hidden_layer_size, num_labels): """ Take in…

Continue Reading## Build Hand Gesture Recognition from Scratch using Neural Network — Machine Learning Easy and Fun

The hidden layer size will be 25 nodes and the output will be 4 nodes (4 type of signs).Defining the…

Continue Reading## Andrew Ng’s Machine Learning Course in Python (Linear Regression)

(https://matplotlib.org/mpl_toolkits/mplot3d/tutorial.html)plt.plot(J_history)plt.xlabel("Iteration")plt.ylabel("$J(Theta)$")plt.title("Cost function using Gradient Descent")Plotting the cost function against the number of iterations gave a nice descending trend, indicating that…

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