Search result for Machine learning and linear algebra Online Courses & Certifications
FollowFilter ![]()
Filter ![]()
Showing 321 courses
By Category ![]()
By Subject![]()
By Language![]()
By Duration![]()
By Price![]()
Get Course Alerts by Email
Financial Engineering and Artificial Intelligence in Python
by Lazy Programmer Team- 4.7
-
![]()
![]()
![]()
![]()
![]()
20 hours on-demand video
Have you ever thought about what would happen if you combined the power of machine learning and artificial intelligence with financial engineering? Convex optimization with Linear Programming and Quadratic Programming In addition, we will look at various non-traditional techniques which stem purely from the field of machine learning and artificial intelligence, such as:...
$199.99
How to Win a Data Science Competition: Learn from Top Kagglers
by Dmitry Ulyanov , Alexander Guschin , Mikhail Trofimov , Dmitry Altukhov , Marios Michailidis- 4.7
-
![]()
![]()
![]()
![]()
![]()
Approx. 54 hours to complete
- Gain experience of analysing and interpreting the data. - Master the art of combining different machine learning models and learn how to ensemble. Disclaimer : This is not a machine learning course in the general sense. - Machine Learning: basic understanding of linear models, K-NN, random forest, gradient boosting and neural networks....
Combining and Analyzing Complex Data
by Richard Valliant, Ph.D.- 4.2
-
![]()
![]()
![]()
![]()
![]()
Approx. 10 hours to complete
In this course you will learn how to use survey weights to estimate descriptive statistics, like means and totals, and more complicated quantities like model parameters for linear and logistic regressions. Linear Models Linear Models in Stata Impact of Research on Innovation, Competition and Science Machine Learning and Record Linkage (Winkler 2011)...
Remote Sensing Image Acquisition, Analysis and Applications
by John Richards- 4.5
-
![]()
![]()
![]()
![]()
![]()
Approx. 23 hours to complete
Module 2 Lecture 1: Fundamentals of image analysis and machine learning Module 2 Lecture 14: Deep learning and the convolutional neural network, part 1 Module 2 Lecture 15: Deep learning and the convolutional neural network, part 2 Module 2 Lecture 16: Deep learning and the convolutional neural network, part 3 Week 13 Lectures and Quiz...
Data Science & Deep Learning for Business™ 20 Case Studies
by Rajeev D. Ratan- 4.2
-
![]()
![]()
![]()
![]()
![]()
20 hours on-demand video
Machine Learning Theory - Linear Regressions, Logistic Regressions, Decision Trees, Random Forests, KNN, SVMs, Model Assessment, Outlier Detection, ROC & AUC and Regularization Big Data with PySpark - Challenges in Big Data, Hadoop, MapReduce, Spark, PySpark, RDD, Transformations, Actions, Lineage Graphs & Jobs, Data Cleaning and Manipulation, Machine Learning in PySpark (MLLib) Unsupervised Machine Learning with K-Means, Mean-Shift, DBSCAN, EM with GMMs, PCA and t-SNE...
$9.99
Convex Optimization
by Stephen Boyd , Henryk Blasinski- 0.0
-
![]()
![]()
![]()
![]()
![]()
8 Weeks
This course concentrates on recognizing and solving convex optimization problems that arise in applications. The syllabus includes: convex sets, functions, and optimization problems; basics of convex analysis; least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems; optimality conditions, duality theory, theorems of alternative, and applications; interior-point methods; applications to signal processing, statistics and machine learn...
Convex Optimization
by Stephen Boyd , Henryk Blasinski- 0.0
-
![]()
![]()
![]()
![]()
![]()
8 Weeks
The syllabus includes: convex sets, functions, and optimization problems; basics of convex analysis; least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems; optimality conditions, duality theory, theorems of alternative, and applications; interior-point methods; applications to signal processing, statistics and machine learning, control and mechanical engineering, digital and analog circuit design, and finance....
Related searches
Applied Machine Learning without coding using Orange 3
by Yannis Faitakis- 4.6
-
![]()
![]()
![]()
![]()
![]()
10 hours on-demand video
This is a course about data science and machine learning without using any programming! You do not need to have any background in machine learning in order to follow this course. I provide resources for further reading if you want to advance your knowledge in machine learning and data science. Modelling for both classification and regression problems...
$12.99
Real data science problems with Python
by Francisco Juretig- 3.9
-
![]()
![]()
![]()
![]()
![]()
7.5 hours on-demand video
Practice machine learning and data science with real problems This course explores a variety of machine learning and data science techniques using real life datasets/images/audio collected from several sources. Linear regressionPenalized estimatorsClusteringPrincipal components This course aims to ease that transition between knowing machine learning, and doing real machine learning on real situations....
$11.99
Case Studies in Functional Genomics
by Rafael Irizarry , Michael Love , Vincent Carey- 0.0
-
![]()
![]()
![]()
![]()
![]()
5 Weeks
Perform RNA-Seq, ChIP-Seq, and DNA methylation data analyses, using open source software, including R and Bioconductor. We will explain how to perform the standard processing and normalization steps, starting with raw data, to get to the point where one can investigate relevant biological questions. 2x: Introduction to Linear Models and Matrix Algebra...
$149
Previous
