What Will You Learn?
You will learn the essentials of computer vision through deep learning and acquire hands-on experience in implementing algorithms using TensorFlow. This course is tailored for beginners, providing foundational knowledge to apply deep learning techniques to visual data and explore the exciting realm of computer vision.
About This Course
Provider: Youtube
Format: Online
Duration: 34 hours to complete [Approx]
Target Audience: Beginners
Learning Objectives: Upon completion this free course, you will have gained a foundational understanding of computer vision with deep learning, specifically in implementing algorithms using TensorFlow.
Course Prerequisites: NA
Assessment and Certification: NA
Instructor: Freecodecamp
Key Topics: Deep Learning, TensorFlow, Computer Vision, Python Programming, Machine Learning
Topic Covered:
- - Introduction
- - Tensors and Variables
- - Building Neural Networks with TensorFlow [Car Price Prediction]
- - Building Convolutional Neural Networks with TensorFlow [Malaria Diagnosis]
- - Building More Advanced Models in Teno Convolutional Neural Networks with TensorFlow [Malaria Diagnosis]
- - Evaluating Classification Models [Malaria Diagnosis]
- - Improving Model Performance [Malaria Diagnosis]
- - Data Augmentation [Malaria Diagnosis]
- - Advanced TensorFlow Topics [Malaria Diagnosis]
- - Tensorboard Integration [Malaria Diagnosis]
- - MLOps with Weights and Biases [Malaria Diagnosis]
- - Human Emotions Detection
- - Modern Convolutional Neural Networks [Human Emotions Detection]
- - Transfer Learning [Human Emotions Detection]
- - Understanding the Blackbox [Human Emotions Detection]
- - Transformers in Vision [Human Emotions Detection]
- - Model Deployment [Human Emotions Detection]
- - Object Detection with YOLO
- - Image Generation
- - Conclusion
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