This course aims to teach learners how to build neural networks using Python and TensorFlow 2.0. By the end of the course, students will be able to understand the fundamentals of neural networks, load and analyze data, create and utilize models for predictions, perform text classification, work with embedding layers, train models, and save/load models. The course adopts a tutorial-based teaching method and is suitable for individuals interested in learning about neural networks and TensorFlow 2.0.
Overview
Syllabus
Python Neural Networks - Tensorflow 2.0 Tutorial - What is a Neural Network?.
Python Neural Networks - Tensorflow 2.0 Tutorial - Loading & Looking at Data.
Python Neural Networks - Tensorflow 2.0 Tutorial - Creating a Model.
Python Neural Networks - Tensorflow 2.0 Tutorial - Using the Model to Make Predictions.
Python Neural Networks - Tensorflow 2.0 Tutorial - Text Classification P1.
Tensorflow 2.0 Tutorial - What is an Embedding Layer? Text Classification P2.
TensorFlow 2.0 Tutorial - Training the Model - Text Classification P3.
Tensorflow 2.0 Tutorial - Saving & Loading Models - Text Classification P4.
How to Install TensorFlow GPU on Linux.
Taught by
Tech With Tim
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