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Supervised Learning Help

Codersarts is an online programming help platform that provides Supervised Learning assignment, coding assignment, coursework and 1:1 session with expert mentors. Get your Supervised Learning projects and assignments done before deadline or learn from expert mentors with team training & coaching experiences.

Supervised Learning Help

Are you struggling the with completing your machine learning assignment or project using Supervised Learning?

What is Supervised Learning Help?

It is also known as supervised machine learning, subcategory of machine learning and artificial intelligence. In this learning, a system is trained with data that has been labelled. The labels categories each data point into one or more groups, for example yes or no. The system learns how this data – known as training data – is structured, and uses this to predict the categories of new – or ‘test’ – data.


Common tasks in Supervised learning Help.

In supervised learning there are two most common tasks are regression and classification.

  • Regression: In regression understanding the relationship between dependent and independent variables. It is used to predict continuous value such as salary, sales revenue etc.

  • Classification: In classification, classify the data into groups of dependent variables.


How it is helpful for ML Students and Developers, Engineers and AI researchers.

Supervised learning is one of the most powerful techniques that enables artificial intelligence systems to make business decisions faster and more accurately than humans. Supervised learning help to developers or engineer to solve such type of business problems:

  • Reducing customer churn

  • Determining customer lifetime value

  • Personalising product recommendations

  • Forecasting sales

  • Detecting fraud


Important tools, packages and libraries

  • Scikit-learn : It is a free software machine learning library for python programming.

    • Logistic regression

    • KNeighborsClassifier

    • SVC

    • GaussianNB

    • DecisionTreeClassifier

    • RandomForestClassifier

    • AdaBoostClassifier

    • GradientBoostingClassifier

    • XGBClassifier

    • Classification_report

    • confusion_matrix

    • accuracy_score

    • mean_squared_error


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