Deep Learning – Convolutional Neural Networks with TensorFlow
English | Tutorial | Size: 880.4 MB
In this 3 hr course, explore the world of Convolutional Neural Networks (CNNs) using TensorFlow 2. You’ll gain insights into key concepts like convolution, its integration into neural networks, and practical applications in image recognition and natural language processing. Hands-on coding exercises help solidify your understanding for practical deployment.
What I will be able to do after this course
Understand the foundational principles of convolutions and their application in neural networks.
Build Convolutional Neural Networks (CNNs) using TensorFlow 2 with practical examples.
Apply CNN techniques to diverse image recognition datasets, spanning from simple to complex.
Master techniques like batch normalization, data augmentation, and transfer learning for top-notch performance.
Delve into text preprocessing and classification with CNNs in Natural Language Processing (NLP) tasks.
Course Instructor(s)
Lazy Programmer is a seasoned expert in deep learning and machine learning, with extensive experience in building scalable AI solutions. Known for his approachable teaching style, he excels in simplifying advanced topics in Python and TensorFlow. His knowledge is rooted in years of professional experience in AI and data science, making his courses informative and hands-on.
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