
How we'll be learning deep learning/machine learning using keras in this course.
In this lecture we will set up our colab environment before we start working with deep learning.
What is the difference between Artificial Intelligence, Deep Learning and Machine Learning?
What is Linear Regression? This video explains what linear regression is and how it works.
In this video we implement linear regression in keras.
In this video we use a deep neural network in keras to predict housing prices
In this video we use a convolutional neural network in keras to predict handwritten digits.
In this video we use a recurrent neural network in keras to generate text
When I started learning deep learning, I had a hard time figuring out how everything worked. What library was the best for me? Which algorithms worked best for which data set? How could I know my model was accurate? I spent a lot of time on tutorials, courses and reading to try and answer these questions. In the end, I felt like the process I took to learn deep learning was too inefficient. That is why I created this course.
Learn Keras: Build 4 Deep Learning Applications is a course that I designed to solve the problems my past self had. This course is designed to get you up and running with deep learning as quickly as possible. We use keras in this course because it is one of the easiest libraries to learn for deep learning. Each video, we go over a different machine learning algorithm and its use cases. The four algorithms we focus on the most are:
1. Linear Regression
2. Dense Neural Networks
3. Convolutional Neural Networks
4. Recurrent Neural Networks
In conclusion, if you are looking at a quick intro into deep learning, this course is for you.
So what are you waiting for? Let's get started!