Description for TensorFlow 2.0 Practical
Advanced TensorFlow Techniques: Gain practical experience in the utilization of GPUs and TPUs in Google Colab by learning to construct, train, and deploy ANNs using TensorFlow 2.0.
Performance Optimization: Develop proficiency in the training of neural network weights, the optimization of hyperparameters, and the evaluation of model performance using key performance indicators (KPIs) such as Precision, Recall, and Mean Squared Error.
Practical Projects: Participate in real-world projects, such as regression tasks (e.g., house price prediction, sales forecasting) and classification tasks (e.g., diabetes detection, traffic sign classification).
Convolutional Neural Networks: Apply convolutional neural networks (CNNs) to image classification using datasets such as Cifar-10 and comprehend their function in deep learning applications.
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 2
Offered by: On Udemy provided by Dr. Ryan Ahmed, SuperDataScience Team & Ligency Team
Duration: 11h 45m
Schedule: Full lifetime access
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