- Encoder-decoders + more on representation learning
16
- Families of neural networks continued
17
- Are neural networks opaque?
18
- Building up from a neuron to a neural network
19
- A demo of representation learning in TF Playground
20
- Importance of activation functions
21
- What’s a neural network library?
22
- Overfitting and underfitting
23
- Autoencoders and anomaly detection screencast and demo
24
- Book recommendations
Description:
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Dive into a comprehensive 1-hour 14-minute ML Tech Talk that provides an in-depth overview of Deep Learning. Explore representation learning, various neural network families and their applications, and gain insights into the inner workings of deep neural networks. Learn through numerous code examples and key concepts from TensorFlow. Discover the differences between AI, ML, and DL, understand hyperparameters, and explore the skills crucial for machine learning. Examine real-world applications in healthcare, investigate different neural network architectures, and delve into topics like overfitting, underfitting, and autoencoders. Benefit from book recommendations and access a wealth of helpful resources, including demos, tutorials, and additional courses to further your deep learning journey.