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Statistical Learning
by Trevor Hastie , Robert Tibshirani- 0.0
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9 Weeks
The syllabus includes: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (ridge and lasso); nonlinear models, splines and generalized additive models; tree-based methods, random forests and boosting; support-vector machines....
$149
Probabilistic Graphical Models 1: Representation
by Daphne Koller- 4.6
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Approx. 67 hours to complete
Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. Template Models for Bayesian Networks Overview of Template Models Temporal Models - DBNs Temporal Models - HMMs Plate Models Template Models Conditional Random Fields...
Probability and Statistics: To p or not to p?
by Dr James Abdey- 4.6
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Approx. 16 hours to complete
Complexity - The Need for Models Complexity - The Need for Models 3 Expectation of Random Variables 3 Expectation of Random Variables 6 Variance of Random Variables 6 Variance of Random Variables 2 Random Sampling 3 Further Random Sampling 2 Random Sampling 3 Further Random Sampling...
Machine Learning A-Z™: Hands-On Python & R In Data Science
by Kirill Eremenko- 4.5
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44 hours on-demand video
TOP GRADIENT BOOSTING MODELS INCLUDING XGBOOST AND EVEN CATBOOST! Have a great intuition of many Machine Learning models Make robust Machine Learning models Build an army of powerful Machine Learning models and know how to combine them to solve any problem...
$17.99
Machine Learning Classification Bootcamp in Python
by Dr. Ryan Ahmed, Ph.D., MBA- 4.5
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11.5 hours on-demand video
Students who enroll in this course will master machine learning classification models and can directly apply these skills to solve real world challenging problems. Apply advanced machine learning models to perform sentiment analysis and classify customer reviews such as Amazon Alexa products reviews Apply machine learning models to Healthcare applications such as Cancer and Kyphosis diseases classification...
$12.99
Model Thinking
by Scott E. Page- 4.8
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Approx. 27 hours to complete
In this class, I present a starter kit of models: I start with models of tipping points. I move on to cover models explain the wisdom of crowds, models that show why some countries are rich and some are poor, and models that help unpack the strategic decisions of firm and politicians. Randomness and Random Walk Models...
Probabilistic Deep Learning with TensorFlow 2
by Dr Kevin Webster- 4.7
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Approx. 53 hours to complete
This is a crucial aspect when using deep learning models in applications such as autonomous vehicles or medical diagnoses; we need the model to know what it doesn't know. This course follows on from the previous two courses in the specialisation, Getting Started with TensorFlow 2 and Customising Your Models with TensorFlow 2....
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Predictive Analytics using Machine Learning
by Dr Johannes De Smedt , Sofia Varypati , Obinna Unigwe- 0.0
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6 Weeks
Learn how to build predictive models using machine learning. These models form the basis of cutting-edge analytics tools that are used for image classification, text and sentiment analysis, and more. Understand the difference between machine learning and other statistical models Implement the theoretic models in machine learning-based software packages in Python Apply machine learning models to business situations...
$300
Data Mining with Rattle
by Geoffrey Hubona, Ph.D.- 3.8
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15 hours on-demand video
These include: data exploration and visualization; testing data for random variable family characteristics and distributional assumptions; transforming data by scale or by data type; performing cluster analyses; creating, analyzing and interpreting association rules; and creating and evaluating predictive models that may utilize: regression; generalized linear modeling (GLMs); decision trees; recursive partitioning; random forests; boosting; and/or support vector machine (SVM) paradigms....
$11.99
Bayesian Statistics: Techniques and Models
by Matthew HeinerTop Instructor- 4.8
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Approx. 30 hours to complete
Real-world data often require more sophisticated models to reach realistic conclusions. Components of Bayesian models Non-conjugate models Random walk example, Part 1 Random walk example, Part 2 Common statistical models Alternative models Common models and multiple factor ANOVA Predictive distributions and mixture models...
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