Develop essential data science & ai skills with expert instruction and practical examples.
I am sure you heard about neural networks, machine learning and transformers. Maybe you are already familiar with some of the concepts surrounding these fields, or even tried a practical approach already, but still feel you are missing something. I know I have felt this way even after taking several courses and learning special libraries(python I am looking at you).
I always felt I somehow missed the point. That is why I created this hands on course, where together we go over main features of Neural Networks including:LayersNeuronsConnectionsFeed ForwardBackpropagationVisualizing the LossWe will use our own deep neural network diagram, created specifically for this course. Using such graphical approach will make it easier to understand what we are coding, model by model.
Specific emphasis is put on backpropagation, where I guide you through an article with step by step explanations of partial derivatives calculation for our diagram. Once we build our neural network we also test it on more demanding functions and see how we can improve predictions. We use object oriented modelling and a bit of functional programming along the way.
So, if you are interested in a practical coding approach to understanding neural networks, join me in this course.
View pricing and check out the reviews. See what other learners had to say about the course.
Not sure if this is right for you?
Browse More Data Science & AI CoursesExplore more Data Science & AI courses to deepen your skills and advance your expertise.