Search result for Regression models Online Courses & Certifications
FollowFilter ![]()
Filter ![]()
Showing 323 courses
By Category ![]()
By Subject![]()
By Language![]()
By Duration![]()
By Price![]()
Get Course Alerts by Email
The Analytics Edge
by Dimitris Bertsimas , Allison O'Hair , John Silberholz , Iain Dunning- 0.0
-
![]()
![]()
![]()
![]()
![]()
13 Weeks
We will be using the statistical software R to build models and work with data. An applied understanding of mathematical optimization and how to solve optimization models in spreadsheet software...
$199
Applied Machine Learning in R
by Bogdan Anastasiei- 4.5
-
![]()
![]()
![]()
![]()
![]()
8 hours on-demand video
So we’ll talk about supervised and unsupervised machine learning techniques, about the distinctions between prediction and inference, about the regression and classification models and, above all, about the bias-variance trade-off, a crucial issue in machine learning. We’ll start with the regression techniques, where the response variable is quantitative....
$12.99
The Complete Python and JavaScript Course: Build Projects
by Mammoth Interactive- 4.1
-
![]()
![]()
![]()
![]()
![]()
27 hours on-demand video
Learn TensorFlow and how to build models of linear regression. Build stock market prediction models for integration into apps! You'll also learn hands-on Python coding, TensorFlow logistic regression, regression analysis, machine learning, and data science!...
$16.99
Advanced Statistical Inference and Modelling Using R
by Elena Moltchanova- 0.0
-
![]()
![]()
![]()
![]()
![]()
6 Weeks
Extend your knowledge of linear regression to the situations where the response variable is binary, a count, or categorical as well as to hierarchical experimental set-up. This course is directed at people who are already familiar with basic linear regression and fundamentals of statistical inference. Multivariate analysis using Generalised Linear Models (GLMs): Mixed effects linear regression models....
$249
Artificial Intelligence #4:SVM & Logistic Classifier methods
by Sobhan N.- 3.1
-
![]()
![]()
![]()
![]()
![]()
2 hours on-demand video
In machine learning, Support Vector Machines (SVM) are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis. In the terminology of economics, logistic regression is an example of a qualitative response/discrete choice model. Next you go further You will learn how to classify output of model by using Logistic Regression...
$12.99
Complete 2-in-1 Python for Business and Finance Bootcamp
by Alexander Hagmann- 4.7
-
![]()
![]()
![]()
![]()
![]()
37.5 hours on-demand video
Regression (Covariance & Correlation, Linear Regression, Multiple Regression and its pitfalls, Hypothesis Testing of Regression Coefficients, Logistic Regression, ANOVA, Dummy Variables, Links to Machine Learning, Fama-French Factor Models) statsmodels to perform Regression Analysis, Hypothesis Testing and ANOVA Learn Regression (Covariance & Correlation, Linear Regression, Multiple Regression, ANOVA) Learn how to use statsmodels for Regression Analysis and ANOVA...
$16.99
Keras: Deep Learning in Python
by Francisco Juretig- 3.7
-
![]()
![]()
![]()
![]()
![]()
10 hours on-demand video
Do you want to build complex deep learning models in Keras? Keras is the most powerful library for building neural networks models in Python. We also show how to actually bypass Keras, and build the models directly in Theano/Tensorflow syntax (although this is quite complex!)...
$13.99
Related searches
Data Analysis with Python
by Joseph Santarcangelo- 4.7
-
![]()
![]()
![]()
![]()
![]()
Approx. 13 hours to complete
5) Building machine learning Regression models Then we will introduce you to another open-source library, scikit-learn, and we will use some of its machine learning algorithms to build smart models and make cool predictions. Linear Regression and Multiple Linear Regression Polynomial Regression and Pipelines Practice Quiz: Linear Regression and Multiple Linear Regression...
Data Science: Machine Learning and Predictions
by Ani Adhikari , John DeNero , David Wagner- 0.0
-
![]()
![]()
![]()
![]()
![]()
6 Weeks
Learn how to use machine learning, with a focus on regression and classification, to automatically identify patterns in your data and make better predictions. Regression is used when you seek to predict a numerical quantity. Linear regression, correlation, and the phenomenon of regression to the mean How to compare and evaluate the accuracy of machine learning models...
$199
Machine learning with R (RF, Adabost.M1, DT, NB, LR, NN)
by Modeste Atsague- 3.3
-
![]()
![]()
![]()
![]()
![]()
3 hours on-demand video
M1, DecisionTree, Logistic Regression , Naive Bayes, Neural Network, CNN, K-mean , Linear regress How to combine models to predict Missing values treatment ,variables selection and prediction using a linear regression model K mean Clustering ...
$9.99
Previous
