Gain an Introduction to TensorFlow In recent years, computer vision algorithms have made significant advancements, surpassing the human eye's ability to differentiate between images of cats and dogs. Today, even a skilled data scientist armed with just a laptop can accurately classify tens of thousands of objects. This course focuses on utilizing TensorFlow 2.6 to develop, train, and make predictions with models that have driven major breakthroughs in recommendation systems, image classification, and FinTech. Predict with Linear Models You will explore how to leverage TensorFlow 2.6 to make predictions using linear regression models. To apply your knowledge, you will predict house prices in King County. This section of the course also covers loss functions and demonstrates how training linear models in batches can optimize resource utilization. Train Neural Networks The second part of the course delves into using the same tools to make predictions using neural networks. You will gain hands-on experience training a network in TensorFlow by incorporating trainable variables and utilizing your model and test features to predict target values. Combine TensorFlow with the Keras API Expand your skill set by incorporating Keras' powerful API and learn how to combine it with TensorFlow 2.6 to make predictions and evaluate models. By the course's conclusion, you will have a solid understanding of using the Estimators API to streamline model definition and prevent errors. Overall, this course provides a comprehensive introduction to TensorFlow, equipping you with the knowledge and skills to leverage its capabilities in various domains.