Today, we’re holding the second TensorFlow Developer Summit at the Computer History Museum in Mountain View, CA! The event brings together over 500 TensorFlow users in-person and thousands tuning into the livestream at TensorFlow events around the world. The day is filled with new product announcements along with technical talks from the TensorFlow team and guest speakers.
Machine learning is solving challenging problems that impact everyone around the world. Problems that we thought were impossible or too complex to solve are now possible with this technology. Using TensorFlow, we’ve already seen great advancements in many different fields. For example:
Astrophysicists are using TensorFlow to analyze large amounts of data from the Kepler mission to discover new planets. Medical researchers are using ML techniques with TensorFlow to assess a person’s cardiovascular risk of a heart attack and stroke. Air Traffic Controllers are using TensorFlow to predict flight routes through crowded airspace for safe and efficient landings. Engineers are using TensorFlow to analyze auditory data in the rainforest to detect logging trucks and other illegal activities. Scientists in Africa are using TensorFlow to detect diseases in Cassava plants to improving yield for farmers.
Before we get into the fun part of working with data, let’s break down how data science involves more than just statistics, why it’s becoming more important, and the data science process. Data Science vs. Statistics In short, data science is extracting knowledge from data. But how is that different between statistics? Data science encompasses…
