Projekte

• MittelSchwierigkeitsgrad
• 4.3+
• 23.632 Wiederholungen

Dive into agriculture using supervised machine learning and feature selection to aid farmers in crop cultivation and solve real-world problems.

• MittelSchwierigkeitsgrad
• 4.3+
• 13.925 Wiederholungen

Arctic Penguin Exploration: Unraveling Clusters in the Icy Domain with K-means Clustering

• MittelSchwierigkeitsgrad
• 4.3+
• 9.600 Wiederholungen

Build a regression model for a DVD rental firm to predict rental duration. Evaluate models to recommend the best one.

• MittelSchwierigkeitsgrad
• 4.2+
• 2.491 Wiederholungen

Automate e-commerce processes with image classification.

• MittelSchwierigkeitsgrad
• 4.4+
• 10.004 Wiederholungen

Clean customer data and use logistic regression to predict whether people will make a claim on their car insurance!

• MittelSchwierigkeitsgrad
• 4.3+
• 2.674 Wiederholungen

Build a machine learning model to predict if a credit card application will get approved.

• MittelSchwierigkeitsgrad
• 4.5+
• 383 Wiederholungen

Use regression and machine learning models to predict daily power consumption based on temporal factors.

• ExperteSchwierigkeitsgrad
• 4.4+
• 2.165 Wiederholungen

Perform a machine learning experiment to find the best model that predicts the temperature in London!

• ExperteSchwierigkeitsgrad
• 4.5+
• 405 Wiederholungen

Help the bank monitoring their fraud detection model and figuring out why its not performing as expected.

• MittelSchwierigkeitsgrad
• 4.3+
• 1.438 Wiederholungen

Solve the Taxi-v3 environment using Q-learning, ensuring efficient AI-driven transportation.

• ExperteSchwierigkeitsgrad
• 4.3+
• 831 Wiederholungen

Use PySpark to build an e-commerce forecasting model!

• MittelSchwierigkeitsgrad
• 4.3+
• 1.437 Wiederholungen

Join us at a leading insurance company, where well craft a model to predict customer charges and test it with new client data

• ExperteSchwierigkeitsgrad
• 4.4+
• 782 Wiederholungen

Transcribe customer support audio calls, evaluate sentiment, search in text and identify common entities to improve customer service!

• MittelSchwierigkeitsgrad
• 4.1+
• 2.167 Wiederholungen

Use logistic regression to predict whether people will make a claim on their car insurance!

• MittelSchwierigkeitsgrad
• 4.4+
• 703 Wiederholungen

Explore facial recognition with ML by distinguishing Arnold Schwarzenegger from others using Python and scikit-learn.

• MittelSchwierigkeitsgrad
• 4.0+
• 1.343 Wiederholungen

Build models predicting customer churn for Indian telecom customers.

• MittelSchwierigkeitsgrad
• 4.5+
• 803 Wiederholungen

Generate features from text and numeric variables to predict the popularity of books.

• ExperteSchwierigkeitsgrad
• 4.4+
• 678 Wiederholungen

Use logistic regression to determine which treatment procedure is more effective for kidney stone removal.

• MittelSchwierigkeitsgrad
• 4.2+
• 514 Wiederholungen

Help a fast food chain save money and place more accurate orders by building a model to predict food sales.

• ExperteSchwierigkeitsgrad
• 4.2+
• 732 Wiederholungen

Use deep learning to automate the classification of service desk tickets.

• MittelSchwierigkeitsgrad
• 4.4+
• 379 Wiederholungen

Build a regression model for a DVD rental firm to predict rental duration. Evaluate models to recommend the best one.

• MittelSchwierigkeitsgrad
• 4.4+
• 649 Wiederholungen

Leverage machine learning algorithms and models for marketing analytics tasks in a streaming platform.

• MittelSchwierigkeitsgrad
• 4.4+
• 748 Wiederholungen

Automate e-commerce processes with image classification.

• ExperteSchwierigkeitsgrad
• 4.4+
• 379 Wiederholungen

Cluster NBA players by performance stats in the 2022-2023 season.

• MittelSchwierigkeitsgrad
• 4.4+
• 248 Wiederholungen

Improve a Car Price prediction model using Feature Engineering tools

• MittelSchwierigkeitsgrad
• 4.3+
• 324 Wiederholungen

Apply clustering and NLP techniques to sort text data from negative reviews in the Google Play Store into categories.