08.07.2022, 22:47
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Master Deep Learning for Computer Vision with TensorFlow 2
Published 04/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 103 lectures (29h 4m) | Size: 12 GB
Implement Object detection, Image Segmentation, Image Classification, Image Generation & People Counting from scratch!
What you'll learn
Introductory Python, to more advanced concepts like Object Oriented Programming, decorators, generators, and even specialized libraries like Numpy & Matplotlib
Mastery of the fundamentals of Machine Learning and The Machine Learning Developmment Lifecycle.
Linear Regression, Logistic Regression and Neural Networks built from scratch.
TensorFlow installation, Basics and training neural networks with TensorFlow 2.
Convolutional Neural Networks, Modern ConvNets, training object recognition models with TensorFlow 2.
Breast Cancer detection, people counting, object detection with yolo and image segmentation
Generative Adversarial neural networks from scratch and image generation
Requirements
Basic Math
No Programming experience.
Description
In this course, we shall look at core Deep Learning concepts and apply our knowledge to solve real world problems in Computer Vision using the Python Programming Language and TensorFlow 2. We shall explain core Machine Learning topics like Linear Regression, Logistic Regression, Multi-class classification and Neural Networks. If you've gotten to this point, it means you are interested in mastering Deep Learning For Computer Vision and using your skills to solve practical problems.
You may already have some knowledge on Machine learning, computer vision or Deep Learning, or you may be coming in contact with Deep Learning for the very first time. It doesn't matter from which end you come from, because at the end of this course, you shall be an expert with much hands-on experience.
You shall work on several projects like object detection, image generation, object counting, object recognition, disease detection, image segmentation and more, using knowledge gained from this course.
If you are willing to move a step further in your career, this course is destined for you and we are super excited to help achieve your goals!
This course is offered to you by Neuralearn. And just like every other course by Neuralearn, we lay much emphasis on feedback. Your reviews and questions in the forum, will help us better this course. Feel free to ask as many questions as possible on the forum. We do our very best to reply in the shortest possible time.
Here are the different concepts you'll master after completing this course.
Fundamentals Machine Learning.
Essential Python Programming
Choosing Machine Model based on task
Error sanctioning
Linear Regression
Logistic Regression
Multi-class Regression
Neural Networks
Training and optimization
Performance Measurement
Validation and Testing
Building Machine Learning models from scratch in python.
Overfitting and Underfitting
Shuffling
Ensembling
Weight initialization
Data imbalance
Learning rate decay
Normalization
Hyperparameter tuning
TensorFlow Installation
Training neural networks with TensorFlow 2
Imagenet training with TensorFlow
Convolutional Neural Networks
VGGNets
ResNets
InceptionNets
MobileNets
EfficientNets
Transfer Learning and FineTuning
Data Augmentation
Callbacks
Monitoring with Tensorboard
Breast cancer detection
Object detection with YOLO
Image segmentation with UNETs
People counting
Generative modeling with GANs
Image generation
YOU'LL ALSO GET
Lifetime access to This Course
Friendly and Prompt support in the Q&A section
Udemy Certificate of Completion available for download
30-day money back guarantee
Who this course is for
Beginner Python Developers curious about Applying Deep Learning for Computer vision
Computer Vision practitioners who want to learn how state of art computer vision models are built and trained using deep learning.
Anyone who wants to master deep learning fundamentals and also practice deep learning for computer vision using best practices in TensorFlow.
Deep Learning for Computer vision Practitioners who want gain a mastery of how things work under the hood.
ENjoy!!!
Who this course is for
Beginner Python Developers curious about Applying Deep Learning for Computer vision
Deep Learning for Computer vision Practitioners who want gain a mastery of how things work under the hood
Anyone who wants to master deep learning fundamentals and also practice deep learning for computer vision using best practices in TensorFlow.
Computer Vision practitioners who want to learn how state of art computer vision models are built and trained using deep learning.
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