#logistic-regression

Predicting the likelihood of a customer to make repeat purchases using logistic regression
▻https://hackernoon.com/predicting-the-likelihood-of-a-customer-to-make-repeat-purchases-using-l

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Source: FuraffinityFor a business getting a customer is exciting, not only because it helps you ‘secure the bag’ by bringing in much needed revenue, but it also creates an opportunity to create loyalty with this new found customer which in turn could help you ‘secure more bags’ through repeat purchases.Safe BagAssuming your business continues driving and optimising the action(s) that have the biggest positive impact on creating repeat purchases, you create more organic brand ambassadors who will refer friends to your business at no extra cost to you. Additionally, depending on the sizes of the purchases made by these repeat customers, this will increase average customer lifetime value. All things constant, the higher the average lifetime value the more wiggle room you have to spend on (...)

#machine-learning #hackernoon-top-story #exploratory-data-analysis #logistic-regression #data-visualization

Logistic Regression with #tensorflow and #keras
▻https://hackernoon.com/logistic-regression-with-tensorflow-and-keras-83d2487aed89?source=rss---

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Learn logistic regression with TensorFlow and Keras in this article by Armando Fandango, an inventor of AI empowered products by leveraging expertise in deep learning, machine learning, distributed computing, and computational methods. He has also provided thought leadership roles as Chief Data Scientist and Director at startups and large enterprises.This article will show you how to implement a classification algorithm, known as multinomial logistic regression, to identify the handwritten digits #dataset. You’ll use both TensorFlow core and Keras to implement this logistic regression algorithm.Logistic regression with TensorFlowOne of the most popular examples regarding multiclass classification is to label the images of handwritten digits. The classes, or labels, in this example are (...)

#machine-learning #logistic-regression

Logistic Regression in Python from scratch
▻https://hackernoon.com/logistic-regression-in-python-from-scratch-954c0196d258?source=rss----3a

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Logistic Regression in Python (A-Z) from ScratchClassification is a very common and important variant among Machine Learning Problems. Many Machine Algorithms have been framed to tackle classification (discrete not continuous) problems. Examples of classification based predictive analytics problems are:Diabetic Retinopathy: Given a retinal image, classify the image (eye) as Diabetic or Non-Diabetic.Sentiment Analysis: Given a sentence, analyze the sense of the sentence (for ex. happiness/sadness, praise/insult, etc.)Digit Recognition: Given an image of a digit, recognize the digit (0–9). This is an example of Multi-Class Classification.and many more…Problems 1 and 2 are examples of Binary Classification, where there are only 2 classes, Diabetic/Non-Diabetic and Happiness/Sadness or (...)

#data-visualization #data-science #machine-learning #python3 #logistic-regression

Introduction to Machine Learning Algorithms: Logistic Regression
▻https://hackernoon.com/introduction-to-machine-learning-algorithms-logistic-regression-cbdd82d8

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Build your Logistic Regression model from scratchLogistic regression is the most famous machine learning algorithm after linear regression. In a lot of ways, linear regression and logistic regression are similar. But, the biggest difference lies in what they are used for. Linear regression algorithms are used to predict/forecast values but logistic regression is used for classification tasks. If you are shaky on the concepts of linear regression, check this out. There are many classification tasks done routinely by people. For example, classifying whether an email is a spam or not, classifying whether a tumour is malignant or benign, classifying whether a website is fraudulent or not, etc. These are typical examples where machine learning algorithms can make our lives a lot easier. A (...)

#code #tutorial #logistic-regression #machine-learning