Updated Part 4: Convolutional Neural Networks's programme assignments
I will upload the slides and assignments gradually, and if you like this repository, please follow me and give me a star :) (slides are not available right now in the course page). The third course Structuring Machine Learning Projects focuses on the systematic method to improve the performance of Neural Network, while with no programming assignments.
This course is created by deeplearning.ai. Master Deep Learning, and Break into AI
https://www.coursera.org/specializations/deep-learning
cited from the homepage:
If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning.
In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach.
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AI is transforming multiple industries. After finishing this specialization, you will likely find creative ways to apply it to your work.
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