Since the field of AI is getting more complex each and every day, the need for knowledge in a specialize field, such as TensorFlow 2.0, is growing exponentially. This is going on to such an extent that knowing TensorFlow is becoming a fundamental part of working in AI.
- Implement ANN, CNN and RNN in Tensorflow 2.0
- Build your own Transfer Learning application in Tensorflow 2.0
- Serve a TensorFlow model with RESTful API
- Learn how to develop ANNs models and train them in Google’s Colab while leveraging the power of GPUs and TPUs.
- Deploy ANNs models in practice using TensorFlow 2.0 Serving.
- Train Artificial Neural Networks (ANNs) using back propagation and gradient descent methods.
- Apply ANNs to perform regression tasks such as house prices predictions and sales/revenue predictions.
- Apply revolutionary GANs to generate brand new images using Keras API in TF 2.0.
- Train and test Auto-Encoders to perform image compression and de-noising using Keras API in TF 2.0.
- Understand how BERT is different from other standard algorithm and is closer to how humans process languages
- Use the BERT layer as a embedding to plug it to your own NLP model
- Create customs layers and models in TF 2.0 for specific NLP tasks
