Zero to Deep Learning Bootcamp Two - Getting Started With Deep Learning
This Learning Path is the second of three Learning Paths in the Zero to Deep Learning Bootcamp Cloud Academy has developed in collaboration with Deep Learning expert Francesco Mosconi from Calalit. The Zero to Deep Learning Bootcamp has been developed to help you master Deep Learning in an interactive, self paced format.
Anyone interested in getting started with practical applications of Data Science and Deep Learning. Whether you're just starting out with machine learning or a more experienced data scientist looking to throw deep learning into the mix, this Learning Path will provide the necessary skills to serve as a solid foundation for you to continue learning after the course has been completed.
- Understand the core principles of deep learning
- Recognize and explain the concept of Neural Networks
- Recognize and explain how linear and non-linear problems can be solved using Neural Networks
We recommend completing the Zero to Deep Learning Bootcamp One - Introduction to Data Science and Machine Learning Learning Path prior to starting this Learning Path.
This Learning Path is made up of 12 expertly instructed lectures along with 4 exercises and their respective solutions.
We welcome all feedback so please direct any comments or questions on this course to us at firstname.lastname@example.org.
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.