This complete course on ‘Artificial Intelligence’ covers all the basics of neural network-based models.
Gain a conceptual understanding of learning mechanisms such as the need and history of neural networks, gradient, forward spread, loss functions and their implementation through Python libraries.
Learn some essential concepts related to deep neural networks that also work with Google's powerful Tensorflow library that comes with pre-built Keras. All the theoretical and practical aspects of this subject will be covered in depth.
Dive deeper into the math behind each concept to understand its details.
We will conclude with a neural network model for classification using the MNIST data set. Learn its application in business or real-life issues in other domains.
- ✔️Activation functions
- ✔️Softmax function
You can take this course for free and access its video content and resources. At the end if you want to acquire a certificate you will have to pay.
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