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"Building a Binary Classification Model in Azure ML"-Ref.:Udemy.com, Binary Classification Model, Azure ML, Azure



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"Building a Binary Classification Model in Azure ML"-Ref.:Udemy.com
 Reference: https://www.udemy.com/building-a-binary-classification-model-in-azure-ml/
   
" * What's the probability you'd live or die on the Titanic? * What Will I Learn? * You'll be able to use Azure ML to build a binary classification model from end to end. * You'll understand how to score and evaluate a binary classification model. * You'll use what you've learned to predict whether you would have lived or would have died if you were aboard the Titanic. * Curriculum For This Course - Lectures * Course Introduction * An Introduction to the Course * What are we seeking to accomplish? * Creating Our Titanic Data Set * The Modeling Process * Defining Our Categorical Variables * Renaming Our Columns * Clean Missing Age Values * Remove Unnecessary Columns * Specify Our Response Class * Building the Model * Analyzing The Results * Adding a Second Model for Comparison * Analyzing the Results * What is Cross Validation? * Cross Validating Our Results * Tuning the Model * Publish To Web Service * Requirements * A basic understanding of Azure Machine Learning. * A high level understanding of machine learning. * Description * First impressions are Finally, a practicing educator" Course delivery is smooth and spot on. Right before you lose hope a gem like this pops up - thanks." - Don Councill * * Welcome to Building a Binary Classification Model in Azure ML. * * Microsoft’s goal of democratizing machine learning is taking shape. * * Taking predictive analytics to public cloud seems like the next logical step towards large-scale consumerization of Machine Learning. Azure ML does just that, while making it significantly easier for the developers to build high probability machine learning models without a PhD in statistics. * * In this course, we are going to build one of the simplest and most common models, the binary classification model. * * The goal of binary classification is to categorize data points into one of two buckets: 0 or 1, true or false and to survive or not to survive. * * Many decisions in life are binary, answered either Yes or No. Many business problems also have binary answers. For example: “Is this transaction fraudulent?”, “Is this customer going to buy that product?”, or “Is this user going to churn?” In machine learning, this is called a binary classification problem. * * We will use binary classification to predict the probability of someone surviving if they had been aboard the Titanic. * * We are going to create an end to end workflow. We will download the data set, clean it, model it, evaluate it then publish our results so others can use it. * * Upon completing the course you’ll know how to create a model that accurately predicts the survivability of an individual based on attributes in the data set. * * You’ll gain insight into the vernacular used in machine learning. * * For example, in the last sentence I used the world ‘attribute.’ An attribute in machine learning is no different than a column in a data set. * * Various attributes affect the outcome of the prediction. For example, my chance of survival was 21.07% if I would have been in first class. If I would have been in second class my changes dropped to 2.16%. Either way, I wouldn't have made it. * * Thanks for your interest in Building a Binary Classification Model in Azure ML.. We will see you in the course!!! * * Who is the target audience? * If you want to make the jump from developer, DBA or Data Analyst to Data Scientist then this course is for you. * This course is for those who are learning machine learning on the Azure ML Platform. " - Ref.: Udemy.com 


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