Learning Path

Tensorflow 2.0 Skill Track

A TensorFlow specialist utilizes the vast knowledge of the TensorFlow library to create everything from neural networks to chat bots as a means to solve a myriad of problems in data science.

5 Courses
49 Hours in Total
10 Case Studies
Lifetime access to course Content

Market Opportunity

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.

Career Opportunity

A TensorFlow specialist’s average annual salary is $148,508 in the United States (source: ZipRecruiter)

Rare skills

What You Will Learn

  • 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
A Complete Guide on TensorFlow 2.0 using Keras API
1
13 hours
TensorFlow 2.0 Practical
2
12 hours
TensorFlow 2.0 Practical Advanced
3
13 hours
Modern Natural Language Processing in Python
4
6 hours
Learn BERT - most powerful NLP algorithm by Google
5
5 hours

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