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
Joshua Akosadevwithjosh.com·Aug 8, 2023Supervised Learning Performance Measurement: Regression ModelsIntroduction Let's quickly review the two categories of supervised learning models: regression models and classification models. Regression models predict a continuous dependent variable, such as an integer result. On the other hand, classification m...Discuss·21 likes·40 readsAI
Ayesha Irshadayeshairshad.hashnode.dev·Aug 7, 2023Unleashing the Power of Machine Learning with Python: Scikit-learn, TensorFlow, and KerasUnleashing the Power of Machine Learning with Python: Scikit-learn, TensorFlow, and Keras Machine Learning has revolutionized various industries, from healthcare to finance, by enabling systems to learn from data and make intelligent decisions. Pytho...DiscussMachine Learning
Isheunesu Temboisheunesu.hashnode.dev·Jul 17, 2023Introduction To Scikit-Learn PipelineLet’s say you are a machine learning engineer and you are hired to create a machine learning algorithm by the bank to determine fraudulent transactions to save their customers from loosing money . l guess what you would do is to try out different mac...DiscussMachine Learning
Isheunesu Temboisheunesu.hashnode.dev·Jul 17, 2023Cross-Validation Using K-Fold With Scikit-LearnImagine that you are a medical research scientist and your task is to find a cure for a particular disease , you perform experiments and test the drug on animals before you administer it to humans . The same happens with machine learning we train the...DiscussMachine Learning
Rounak Showrounakshow.hashnode.dev·Apr 28, 2023Normalization and Standardization with Python CodeTo build a good Machine Learning model, Feature Engineering is a crucial step. During Data Preprocessing, we do feature engineering so that our data will be perfect for the model-building. Feature Engineering includes many scaling techniques such as ...Discuss·68 readsStatistics for Data ScienceData Science
Muhammad Kadirkaymohh.hashnode.dev·Apr 22, 2023Step-by-Step Guide: How to Build a Simple Machine Learning Model Using Scikit-LearnAre you tired of constantly Googling the price of your favorite stocks or cryptocurrencies? Have you ever wondered how you could use machine learning to predict their future values? Well, look no further! In this article, we will dive into building a...DiscussMachine Learning
Emmanuel Ogebeemmanuelogebe.hashnode.dev·Apr 19, 2023Nigerian Movie Recommendation System: A Machine Learning ProjectAbstract Nollywood movies are referred to as “Nollywood” because they were produced in Nigeria utilizing a type of video equipment known as a “Nolly,” which was thought to be an acronym for “Nigeria” or “National Optical Lens.” The Nigerian Movie I...Discuss·3 likes·254 readsProjectsMachine Learning
satish Mishratechtonics.hashnode.dev·Apr 7, 2023Demystifying fit_transform and transform in Scikit-learn: Which Method to Use for Data Preprocessing and When?Machine learning models often require data preprocessing before being trained. Preprocessing involves transforming the raw data into a format that is more suitable for machine learning algorithms. In scikit-learn, there are two methods used for data ...Discuss·66 readsMachine Learning
Barry Ugochukwuwritemlcode.hashnode.dev·Mar 15, 2023What Are Learning Curves and Why You Should Care About ThemBefore we begin make sure you check the previous article in this series here How do we know if our models are learning well or not? How do we measure their performance and improvement over time? How do we diagnose and fix common problems such as unde...Discuss·31 readsExpert Tips to Optimize Machine Learning Model Performance and Boost Accuracy #LearningCurve
