Harshita Dokiharshita75.hashnode.dev·Nov 4, 2023Rock vs Mine Prediction Model: A Logistic Regression AnalysisPredictive modeling plays a crucial role in a wide range of applications, from finance to healthcare. In this blog post, we'll explore a logistic regression model that I've developed to distinguish between rocks and mines. We'll discuss the model's a...DiscussMachine Learning
Saurabh Naiksaurabhz.hashnode.dev·Oct 1, 2023Logistic Regression : From Probabilities to PredictionsIntroduction: In the world of machine learning and statistics, Logistic Regression stands as a powerful and versatile tool for classification tasks. Despite its name, it's not just about regression; rather, it's a method for estimating probabilities ...DiscussML algorithm intuitions with essential conceptsMachine Learning
Sakinah Emoshioke Alisakinahai.hashnode.dev·Sep 29, 2023A Simple Understanding of Linear Regression and Logistic RegressionThe concept of AI from a layman’s view seems complex just like trying to understand the Big Bang theory. This is only sometimes the case. AI isn’t always complex and has already been infused in mundane activities. AI for years has continued to solve ...DiscussMachine Learning
Luis Jose Mendez mendezluisjose.hashnode.dev·Sep 21, 2023Breast Cancer Predictor with Scikit Learn, Streamlit and Deployed with Flask and AWSBinary Classification Breast Cancer Model with Scikit Learn, Streamlit, Flask and AWS The Model was trained with Tabular Breast Cancer Data and with the Logistic Regression Scikit-Learn Architecture. The Model predicts if a given cell is either Benig...Discussscikit learn
Ahameddatailm.hashnode.dev·Sep 21, 2023Optimizing Model Selection with Cross-Validation in Scikit-LearnWhen choosing between different machine learning algorithms for a task, try multiple models and use cross-validation to evaluate their performance. Sklearn provides a convenient way to do this. Here's a sample code snippet: from sklearn.model_selecti...DiscussMachine LearningMachine Learning
Areen 👽hxruchiyo.hashnode.dev·Sep 20, 2023ML Algo 3Introduction Logistic Regression holds an important position in the world of Machine Learning because of its effectiveness in binary classification tasks. Despite its name, it's not a regression algorithm but rather a powerful tool for estimating pro...Discuss·1 likeMachine Learning
Akhil Soniakhilworld.hashnode.dev·Aug 29, 2023Train Logistic Regression ModelIn one of my articles, I have already discussed training of a linear regression model. Training a model means setting its parameters so that the model best fits the training set. Best fitting the training set means that the performance measure cost f...Discuss·10 likesMachine Learning
Temiloluwa Oloyetemiloluwaoloye.hashnode.dev·Aug 16, 2023Sentiment Analysis Using Logistic RegressionIntroduction Sentiment analysis is a set of processes for classifying the emotions behind texts. Usually, we classify these emotions into three – Positive, Negative, and Neutral. For example, a tweet,” I am feeling happy today” is positive; “I am fee...Discuss·7 likes·66 readsnatural language processing
Kenneth Akpocoderofph.hashnode.dev·Aug 10, 2023Navigating Binary Classification with Logistic Regression: A Visual Journey into Binary ClassificationIntroduction Logistic regression, despite its name, isn't a technique for solving logistics challenges. Instead, it's a powerful statistical method used for binary classification problems. Whether you're stepping into the world of data science, machi...DiscussData Science
Nafs AhmadforZaycodes Publicationzaycodes-1686045136273.hashnode.dev·Jul 31, 2023Churn Prediction: Building a bank customer churn prediction model using machine learningPrerequisite This article serves as a resource for individuals looking to gain insights into churn prediction, machine learning techniques, and their applications in the banking sector. To follow this article, readers should have: Knowledge of Pytho...Discuss·1 likeMachine Learning
