Introduction To TensorFlow — TF Dev Summit 2019

Introduction To TensorFlow — TF Dev Summit 2019

Transcript

1. Introduction To TensorFlow +OlayinkaPeterOluwafemi @olayinkapeter_
2. What is TensorFlow? TensorFlow is an open source library for numerical computation and large-scale machine learning.
3. You must have come across words like: • Artificial intelligence • Machine learning • Neural network • Deep learning
4. Artificial Intelligence: A field of computer science that aims to make computers achieve human-style intelligence. There are many approaches to reaching this goal, including machine learning and deep learning. • Machine Learning: A set of related techniques in which computers are trained to perform a particular task rather than by explicitly programming them. • Neural Network: A construct in Machine Learning inspired by the network of neurons (nerve cells) in the biological brain. Neural networks are a fundamental part of deep learning, and will be covered in this course. • Deep Learning: A subfield of machine learning that uses multi-layered neural networks. Often, “machine learning” and “deep learning” are used interchangeably.
5. GCP offers four main kinds of services: storage big data machine learning compute
6. Machine learning on Google Cloud Platform
7. Generic task Custom task Stuff someone has solved before Very specific to your dataset “puppy” “Sylvester” Input to prediction
8. Generic task Custom task Stuff someone has solved before Very specific to your dataset Pre-trained models (Machine Learning APIs) Cloud Machine Learning Engine Application developers Data scientists and ML practitioners
9. Identify your own puppy among hundreds of puppies “Sylvester” “Driver” here could be referred to as ‘taxi driver’, for example Importance of specific prediction or translation
10. • Cloud ML Engine allows you to build, train, and serve custom models with your own data
11. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications.
12. bit.ly/gcdcado-tensorflowlab