Search result for Examples of supervised learning Online Courses & Certifications
FollowFilter ![]()
Filter ![]()
Showing 2,722 courses
By Category ![]()
By Subject![]()
By Language![]()
By Duration![]()
By Price![]()
Get Course Alerts by Email
Neural Networks and Deep Learning
by Andrew NgTop Instructor , Kian KatanforooshTop Instructor , Younes Bensouda MourriTop Instructor- 4.9
-
![]()
![]()
![]()
![]()
![]()
Approx. 23 hours to complete
In the first course of the Deep Learning Specialization, you will study the foundational concept of neural networks and deep learning. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology....
Practical Introduction to Machine Learning with Python
by Madhu Siddalingaiah- 4.5
-
![]()
![]()
![]()
![]()
![]()
4.5 hours on-demand video
Quickly Learn the Essentials of Artificial Intelligence (AI) and Machine Learning (ML) Machine learning is an exciting and rapidly growing field full of opportunities. There are a number of machine learning examples demonstrated throughout the course. July 2019 course updates include lectures and examples of self-supervised learning. Tensorflow 2 is one of the most popular machine learning frameworks used today....
$12.99
Introduction to AI, Machine Learning and Data Science 2021
by Pradeep D- 3.8
-
![]()
![]()
![]()
![]()
![]()
32 mins on-demand video
Introductory Course for Beginners to AI, Machine Learning, Data Science, Deep Learning, Supervised and Unsupervised ML This course gives introduction to to AI, Machine Learning, Data Science, Deep Learning, Supervised and Unsupervised learning with real time examples where machine learning can be applied to solve or simplify real world business problems....
$14.99
Python and Machine Learning for Asset Management
by John Mulvey - Princeton University , Lionel Martellini, PhD- 3
-
![]()
![]()
![]()
![]()
![]()
Approx. 17 hours to complete
Then, we will see how this new insight from Machine learning can complete and improve the relevance of the analysis. Supervised learning Machine learning techniques for robust estimation of factor models References for module 2"Machine learning techniques for robust estimation of factor models" Learn the principles of supervised and unsupervised machine learning techniques to financial data sets...
Machine Learning Algorithms: Supervised Learning Tip to Tail
by Anna Koop- 4.7
-
![]()
![]()
![]()
![]()
![]()
Approx. 9 hours to complete
This course takes you from understanding the fundamentals of a machine learning project. Learners will understand and implement supervised learning techniques on real case studies to analyze business case scenarios where decision trees, k-nearest neighbours and support vector machines are optimally used. The Regression side of Supervised Learning Basics of Support Vector Machines...
Introduction to Applied Machine Learning
by Anna Koop- 4.7
-
![]()
![]()
![]()
![]()
![]()
Approx. 7 hours to complete
By the end of the course, you will be able to clearly define a machine learning problem using two approaches. This is the first course of the Applied Machine Learning Specialization brought to you by Coursera and the Alberta Machine Intelligence Institute. The Three Kinds of Machine Learning Semi Supervised Learning (required)...
Data Science for Business Innovation
by Marco Brambilla , Emanuele Della Valle- 4.2
-
![]()
![]()
![]()
![]()
![]()
Approx. 7 hours to complete
The course is a compendium of the must-have expertise in data science for executive and middle-management to foster data-driven innovation. It discusses the value that Data Science can create, the main classes of problems that Data Science can solve, the difference is between descriptive, predictive and prescriptive analytics, and the roles of machine learning and artificial intelligence....
Related searches
Building Deep Learning Models with TensorFlow
by Samaya Madhavan , JEREMY NILMEIER , Romeo Kienzler , Alex Aklson- 4.4
-
![]()
![]()
![]()
![]()
![]()
Approx. 13 hours to complete
The majority of data in the world is unlabeled and unstructured. Deep networks are capable of discovering hidden structures within this type of data. In this course you’ll use TensorFlow library to apply deep learning to different data types in order to solve real world problems. Introduction to Deep Learning Supervised Learning Models Supervised Learning Models (Cont'd)...
Intermediate Intel® Distribution of OpenVINO™ toolkit for Deep Learning Applications
by Kimberly Karalekas- 0.0
-
![]()
![]()
![]()
![]()
![]()
Approx. 5 hours to complete
The course looks at computer vision neural network models from a variety of popular machine learning frameworks and covers writing a portable application capable of deploying inference on a range of compute devices. The course is targeted for application developers, and places focus on examples and discussion of the development workflow....
Introduction to Trading, Machine Learning & GCP
by Jack Farmer , Ram Seshadri- 4
-
![]()
![]()
![]()
![]()
![]()
Approx. 9 hours to complete
In this course, you’ll learn about the fundamentals of trading, including the concept of trend, returns, stop-loss, and volatility. By the end of the course, you will be able to use Google Cloud Platform to build basic machine learning models in Jupyter Notebooks. Supervised Learning and Regression Supervised Learning with BigQuery ML...
Previous
