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Exercise 4

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1h 13m

Continue the journey to data and machine learning, with this course from Cloud Academy.

In previous courses, the core principles and foundations of Data and Machine Learning have been covered and best practices explained. 

This course gives an informative introduction to deep learning and introducing neural networks.

This course is made up of 12 expertly instructed lectures along with 4 exercises and their respective solutions.

Please note: the Pima Indians Diabetes dataset can be found at this GitHub repository or at Kaggle page mentioned throughout the course.

Learning Objectives

  • Understand the core principles of deep learning
  • Be able to execute all factors of the framework of neural nets

Intended Audience





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.

About the Author
Learning Paths

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.