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Explore and run machine learning code with Kaggle Notebooks | Using data from Housing Prices, Portland, OR
Create a linear regression and logistic regression model in Python and analyze its result. Confidently model and solve regression and classification problems A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning basics course. What is covered in this cour...
For Datasets to considering implementing supervised learning: Linear regression. I recommend going onreddit/datasetsorKaggle, to practice and see how accurate of a prediction you can create.
informatics Article Tagging Users' Social Circles via Multiple Linear Regression Hailong Qin 1, Jing Liu 2, Chin-Yew Lin 2 and Ting Liu 1,* 1 Harbin Institute of Technology, Harbin 150001, China; liuting@ir.hit.edu.cn 2 Microsoft Research Asia, Beijing 100086, China; liudiani@microsoft....
The results show that it significantly improved the TPR of generalized linear models, such as L-SVM, LDA, and Logistic regression, which run fast but pursue data points being linearly separable on the whole. With Nyström method, the TPR of these models were promoted by more than 15%. ...
Open Source Fast Scalable Machine Learning API For Smarter Applications (Deep Learning, Gradient Boosting, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, Stacked Ensembles...) - billyfung/h2o-3
Key Tasks: - Use multiple linear regression and descriptive analysis to interpret the data - Apply various descriptive statistical methods, including mean, median, mode, standard deviation, variance, frequency distribution and percentage - Test specific hypotheses based on the survey results Ideal Skills...
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