Search result for Theory of deep learning Online Courses & Certifications
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Introduction to Deep Learning
by Evgeny Sokolov , Зимовнов Андрей Вадимович , Alexander Panin , Ekaterina Lobacheva , Nikita Kazeev- 4.5
Approx. 34 hours to complete
The course starts with a recap of linear models and discussion of stochastic optimization methods that are crucial for training deep neural networks. In the course project learner will implement deep neural network for the task of image captioning which solves the problem of giving a text description for an input image....
Specialized Models: Time Series and Survival Analysis
by Mark J Grover , Miguel Maldonado- 4.5
Approx. 11 hours to complete
This course introduces you to additional topics in Machine Learning that complement essential tasks, including forecasting and analyzing censored data. Deep Learning and Survival Analysis Forecasts Deep Learning - Part 1 Deep Learning - Part 2 Deep Learning - Part 3 Deep Learning Notebook - Part 1 Deep Learning Notebook - Part 2 Deep Learning for Forecasting Demo (Activity)...
Take the Lead on Healthcare Quality Improvement
by Mary A. Dolansky, PhD, RN , Shirley Moore, PhD, RN, FAAN , Mamta K Singh, MD, MS- 4.4
Approx. 30 hours to complete
In this course you will learn about the importance of quality in healthcare and how you can contribute by implementing a quality improvement (QI) project to improve processes of care and patient outcomes. Theory Video Theory Learning Objectives Learning Objectives Theory Theory Learning Objectives Learning Objectives Theory Theory Learning Objectives The Science of Improvement: Setting Aims...
Computer Vision
by Sebastian Thrun , Cezanne Camacho , Alexis Cook , Juan Delgado , Jay Alammar , Ortal Arel , Luis Serrano- 0.0
3 Months
Write programs to analyze images, implement feature extraction, and recognize objects using deep learning models. Learn cutting-edge computer vision and deep learning techniques—from basic image processing, to building and customizing convolutional neural networks. Work on a variety of computer vision and deep learning applications from basic image processing to automatic image captioning....
Intro to Deep Learning with PyTorch
by Luis Serrano , Alexis Cook , Soumith Chintala , Cezanne Camacho , Mat Leonard- 0.0
Approx. 2 months
Deep learning is driving the AI revolution and PyTorch is making it easier than ever for anyone to build deep learning applications. In this course, you’ll gain practical experience building and training deep neural networks using PyTorch. Learn the basics of deep learning and implement your own deep neural networks with PyTorch...
Free
Deep Learning and Reinforcement Learning
by Mark J Grover , Miguel Maldonado- 4.7
Approx. 14 hours to complete
This course introduces you to two of the most sought-after disciplines in Machine Learning: Deep Learning and Reinforcement Learning. Deep Learning is a subset of Machine Learning that has applications in both Supervised and Unsupervised Learning, and is frequently used to power most of the AI applications that we use on a daily basis....
Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
by Andrew NgTop Instructor , Kian KatanforooshTop Instructor , Younes Bensouda MourriTop Instructor- 4.9
Approx. 22 hours to complete
In the second course of the Deep Learning Specialization, you will open the deep learning black box to understand the processes that drive performance and generate good results systematically. Practical Aspects of Deep Learning Weight Initialization for Deep Networks Numerical Approximation of Gradients Practical aspects of Deep Learning Deep Learning Frameworks...
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Learning Technologies Foundations and Applications
by Wenhao David Huang- 4.5
Approx. 8 hours to complete
This course, Learning Technologies Foundations and Applications, is one of the two four-week MOOC courses that form part of Instructional Design MasterTrack Certificate. Evaluate learning technology solutions based on Cognitive Load Theory and related multimedia learning design models. Role of Learning Technologies and Career Paths Module 2: The Evolvement of Learning Technologies...
Natural Language Processing
by Luis Serrano , Jay Alammar , Arpan Chakraborty , Dana Sheahen- 0.0
3 Months
Build probabilistic and deep learning models, such as hidden Markov models and recurrent neural networks, to teach the computer to do tasks such as speech recognition, machine translation, and more! Work on a variety of natural language processing techniques. Build models using probabilistic and deep learning techniques and apply them to speech recognition, machine translation, and more!...
Diagnosing Health Behaviors for Global Health Programs
by William Brieger, DrPH- 4.7
Approx. 10 hours to complete
Health behavior lies at the core of any successful public health intervention. While many of such models and frameworks exist, in this course we will review the Health Belief Model, Social Learning Theory, Theory of Reasoned Action, the Trans-Theoretical Model and the PRECEDE Framework. The Health Belief Model and Social Learning Theory Theory of Reasoned Action...