Learn about the importance of gradient descent and backpropagation, under the umbrella of Data and Machine Learning, from Cloud Academy.
From the internals of a neural net to solving problems with neural networks to understanding how they work internally, this course expertly covers the essentials needed to succeed in machine learning.
- Understand the importance of gradient descent and backpropagation
- Be able to build your own neural network by the end of the course
- It is recommended to complete the Introduction to Data and Machine Learning course before starting.
Hey guys welcome back. This video is about Exercise four in section four. This exercise is about Tensorflow playground. Tensorflow playground is a very nice web application from the guys at Tensorflow that provides an interactive environment where you can play with simple fully connected neural nets on very simple data sets. These are two featured data sets where you have to separate groups of points that are blue and orange. So play with it a few minutes. There's no real goal. You don't need to understand the meaning of every knob and button but just to develop a feeling, an intuition about how things work. So there's no real challenge here just feel free to explore, play with it and see what you find. Good luck and see you in the next video.
I am a Data Science consultant and trainer. With Catalit I help companies acquire skills and knowledge in data science and harness machine learning and deep learning to reach their goals. With Data Weekends I train people in machine learning, deep learning and big data analytics. I served as lead instructor in Data Science at General Assembly and The Data Incubator and I was Chief Data Officer and co-founder at Spire, a Y-Combinator-backed startup that invented the first consumer wearable device capable of continuously tracking respiration and activity. I earned a joint PhD in biophysics at University of Padua and Université de Paris VI and graduated from Singularity University summer program of 2011.