ML is an important component of every major tech product today. However, not everything beyond Excel sheets is big data, and not all big data problems require ML. The most important function of ML should be to supplement the product.
KC Ayyagari, Senior Customer Engineer, San Francisco Enterprise Sales, Google Cloud, presented this C2C Deep Dive.
The recording from this session includes:
- (1:50) Introduction to speaker and agenda overview
- (3:45) Live demo of Google Cloud's Vision API and sentiment analysis
- (7:20) Introduction to machine learning and its relation to AI and deep learning
- (8:30) Teaching ML languages by using examples and reducing errors
- (13:00) Example: using deep reinforcement learning for a neural network to play Atari
- (17:40) Comparing ML to normal software development and representing physical problems in data
- (28:35) The dos and don'ts of ML for managers
- (40:45) Case study: predicting weather trends and flight plans with images of clouds
- (47:50) Building a prototype with dataset search engine
- (51:50) Keys to successful machine learning
Extra Credit: