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Overview to Deep Learning

Developed with
Catalit
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Overview
DifficultyBeginner
Duration37m
Students275

Description

In this Zero to Deep Learning course has been expertly created to provide you with a strong foundation in machine learning and deep learning. So whether you're just starting out with your practice of machine learning or you're a more experienced data scientist that is adding deep learning to the mix, this course will provide the necessary skills to serve as a solid foundation for you to continue learning after the course has been completed.

The course will start out covering simple data and structured data, then moving onto images, with sound, with text, and more complex data where deep learning comes to life. By the end of the course, you'll be able to recognize which problems can be solved with deep learning and organize data in a way that can be used by a neural network. Understanding and learning how to build a neural network model, including fully connected, convolutional, and recurrent neural network and train a model using cloud computing, all within this course.

This course is made up of 5 cohesive lectures that start off the journey into Data and Machine Learning with Cloud Academy.

 

Learning Objectives

  • Learn the key principles of data and machine learning
  • Come away with a strong foundation of the subject in order to develop new skills further
  • Understanding and learning how to build neural network models

Intended Audience

  • No prior knowledge of data and machine learning required

 

 

Transcript

Hey, guys, welcome to this Zero to Deep Learning video course. My name is Francesco, and I will be your instructor for this course. The goal of this course is to provide you with a strong foundation in machine learning and deep learning. So whether you're just starting out with your practice of machine learning or you're a more experienced data scientist that is adding deep learning to the mix, I hope I'll provide you with enough information that serves as a solid base for you to continue learning after the course. We'll begin with simple data, structured data, and then we'll deal with images, with sound, with text, and more complex data that really is where deep learning shines. 

By the end of the course, you'll be able to recognize which problems can be solved with deep learning. You'll be able to organize your data in a way that can be used by a neural network. You'll be able to build a neural network model, including fully connected, convolutional, and recurrent neural network. And you'll be able to train a model using cloud computing, which is nowadays so accessible that I'll make sure that you're really able to use it. I'm really excited to bring to you this course. I hope you're excited to get started. So let's get started with section one, introduction.

About the Author

Students745
Courses8
Learning paths3

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.