Data Science and Machine Learning are rapidly growing fields that use scientific methods and processes to extract useful knowledge and insights from data. In this course, Implementing Predictive Analytics with TensorFlow, you will learn foundational knowledge of solving real-world data science problems. First, you will explore the basics of implementing supervised learning problems including linear regression and neural networks. Next, you will discover how recommendation systems can be implemented using TensorFlow. Finally, you will learn how to understand and implement reinforcement learning systems. When you are finished with this course, you will have the skills and knowledge of TensorFlow needed to solve data science and machine learning problems.
Author Name: Justin Flett
Author Description:
Justin Flett is a Mechatronics Engineer currently working as a Professor within the Faculty of Applied Science and Technology at Sheridan College. Justin has previously held positions at Hydro One Networks, Ford Motor Company, and ABB Robotics spanning across both the electrical and mechanical engineering industries. Most recently, he has been working as an Product Development Professional specializing in training, services, and consultation nation-wide, ranging from design fundamentals to adva… more

Table of Contents

• Course Overview
  1min
• Implementing Supervised Learning Systems
  28mins
• Implementing Recommendation Systems
  26mins
• Implementing Reinforcement Learning Systems
  24mins