Search result for Semantic networks Online Courses & Certifications
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Visual Perception for Self-Driving Cars
by Steven Waslander- 4.7
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Approx. 31 hours to complete
You'll apply these methods to visual odometry, object detection and tracking, and semantic segmentation for drivable surface estimation. Module 3: Feedforward Neural Networks Lesson 1: Feed Forward Neural Networks Lesson 6: Convolutional Neural Networks Supplementary Reading: Feed-Forward Neural Networks Supplementary Reading: Convolutional Neural Networks Feed-Forward Neural Networks Lesson 2: 2D Object detection with Convolutional Neural Networks...
Knowledge-Based AI: Cognitive Systems
by Ashok Goel , David Joyner- 0.0
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Approx. 7 weeks
At the conclusion of this class, you will be able to accomplish three primary tasks. First, you will be able to design and implement a knowledge-based artificial intelligence agent that can address a complex task using the methods discussed in the course. Second, you will be able to use this agent to reflect on the process of human cognition....
Free
Deep Learning in Computer Vision
by Anton Konushin , Alexey Artemov- 3.8
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Approx. 13 hours to complete
Computing semantic image embeddings using convolutional neural networks Employing indexing structures for efficient retrieval of semantic neighbors Attentional cascades and neural networks Action classification with convolutional neural networks Generative adversarial networks Image transformation with neural networks...
Deep Learning with Caffe 2 - Hands On!
by Packt Publishing- 3.5
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4 hours on-demand video
This course teaches you to create, train, and deploy your neural networks and deep learning models using Caffe 2. You will also learn how to create Convolutional Neural Networks (CNNs) that can identify not only handwriting but also fashion items from an image. His research interests are in deep learning and its applications in computer vision such as semantic segmentation....
$9.99
The Complete Guide to TensorFlow 1.x
by Packt Publishing- 4
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2.5 hours on-demand video
Moving ahead, you will dive into neural networks and see how convolution, recurrent, and deep neural networks work and the main operation types used in building them. He has done research on high performance computing since 2005 and began studying and implementing convolutional neural networks in 2008, writing a CPU and GPU supporting neural network feed-forward stage....
$9.99
Convolutional Neural Networks
by Andrew NgTop Instructor , Kian KatanforooshTop Instructor , Younes Bensouda MourriTop Instructor- 4.9
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Approx. 35 hours to complete
By the end, you will be able to build a convolutional neural network, including recent variations such as residual networks; apply convolutional networks to visual detection and recognition tasks; and use neural style transfer to generate art and apply these algorithms to a variety of image, video, and other 2D or 3D data....
R: Neural Nets and CNN Architecture in R - Masterclass!
by Packt Publishing- 3.6
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6 hours on-demand video
Here we understand how Neural Networks work and the benefits they offer for supervised and well as unsupervised learning before building our very own neural network. Finally, we take a look at Artificial Neural Networks and understand how to build your own ANN. His research interests include machine learning, deep learning, the semantic web, linked data, big data, and bioinformatics....
$11.99
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The Outcomes and Interventions of Health Informatics
by Harold P. Lehmann, MD, Ph.D. , Paul Nagy, PhD, FSIIM- 4.5
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Approx. 7 hours to complete
Semantic Networks...
Natural Language Processing with Probabilistic Models
by Younes Bensouda Mourri , Łukasz Kaiser , Eddy Shyu- 4.7
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Approx. 28 hours to complete
Word embeddings with neural networks...
Advanced Computer Vision with TensorFlow
by Laurence Moroney , Eddy Shyu- 4.8
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Approx. 24 hours to complete
In this course, you will: a) Explore image classification, image segmentation, object localization, and object detection. Apply transfer learning to object localization and detection. b) Apply object detection models such as regional-CNN and ResNet-50, customize existing models, and build your own models to detect, localize, and label your own rubber duck images....
